The Dual Nature of Directional Particles in Academic Phrasal Verbs: A Constructionist Corpus Analysis of 'Out', 'Up', and 'Down' in the BAWE Corpus

The Dual Nature of Directional Particles in Academic Phrasal Verbs: A Constructionist Corpus Analysis of 'Out', 'Up', and 'Down' in the BAWE Corpus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Dual Nature of Directional Particles in Academic Phrasal Verbs: A Constructionist Corpus Analysis of 'Out', 'Up', and 'Down' in the BAWE Corpus Tahir Qayyum, Anam Tahir, Shahida Khalique, Nouman Hamid, Syed Atif Amir Gardazi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7222728/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study employs Construction Grammar and cognitive linguistic frameworks to investigate the dual semantic functions of directional adverbial particles ('out', 'up', 'down') within phrasal verbs in the context of English academic writing. Utilizing Corpus Query Language (CQL) within Sketch Engine, a total of 9,866 instances of phrasal verbs from the British Academic Written English (BAWE) corpus were analyzed. The results demonstrate that 78.25% of these usages are idiomatic, with significant variation observed across different genres (χ² = 892.4, p < .001). Notably, 'out' exhibits an idiomatic usage rate of 98.4%, whereas "down' remains predominantly compositional at 63.2%. It is recommended that corpus-based examples, contextual learning, and genre-specific instruction be utilized to facilitate the acquisition of phrasal verbs. The findings substantiate the notion that targeted instruction of phrasal verbs can enhance the academic writing skills of learners of English as a second language. This research integrates corpus linguistics with Construction Grammar (Goldberg, 2006 ) and cognitive semantics (Lakoff, 1987) to explore directional particles as schematic constructions. Within this framework, literal usages preserve their spatial semantics, whereas idiomatic extensions exemplify metaphorical mappings. Phrasal Verbs Adverbial Particles Corpus Linguistics L2 Acquisition Idiomatic and Compositional Particles Academic Writing Construction Grammar EAP Pedagogy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Although phrasal verbs are regarded as complete and meaningful constructions in themselves, they possess a dynamic nature in composition, and this dynamism plays a significant semantic role. It has also been frequently observed that the constituents of phrasal verbs, specifically adverbial particles, are often overlooked in studies of phrasal verbs, even though they play a crucial role in forming multiword expressions centered around verbs and contribute to their meanings. The dual nature of the particles encompasses both a compositional aspect, where they play a crucial role in the meaning-making of the verb, and a frozen aspect, where the meanings are essentially idiomatic; individual words do not contribute significantly to the overall meaning. As a small functional unit, an adverbial particle, whether a preposition or an adverb, is considered to modify the meanings of verbs within phrasal verb constructions. Thornbury’s ( 2002 ) classification of phrasal verbs into four categories, namely, intransitive, transitive separable, transitive inseparable, and three-part, remains a syntactic classification. Semantically, Celce-Murcia and Larsen-Freeman ( 1999 ) have classified phrasal verbs into three types: literal, where the composition helps identify meanings; aspectual, in which meanings remain opaque or partially transparent; and thoroughly idiomatic, where meanings do not depend on any of the constituent parts (Zamin et al., 2019 ). This study is based on two main categories: compositional and frozen particles. The compositional adverbial particles contribute to the overall meaning of the construction, as demonstrated by the phrase “take out.” For example, in the construction "take me out of this room,” it is classified as compositional because "take" retains its meaning while "out" indicates an outward direction. Conversely, frozen particles are involved in the formation of idiomatic expressions, where the meanings of the core constituents are significantly altered, making it impossible to deduce the overall meanings from the individual verb or particle. For example, “break down” is a phrasal verb whose meanings may not be dependent on the verb “break” and the particle “down,” suggesting a downward direction. Nevertheless, there are phrasal verbs, such as “go up” and “take down,” that exhibit both compositional and frozen characteristics, which present a challenge for second language learners. They find it difficult to determine when the same particle acts as a fixed element versus a compositional component. This issue has been a central concern of this study, which focuses on second language acquisition and pedagogy. Initial studies such as Biber et al. ( 1999 ) speculate that for Second Language (L2) learners, compositional phrasal verbs are more accessible to acquire due to their prior knowledge of the meanings of the constituents within the construction. The phrasal verb “go up,” as exemplified in “prices go up,” is more readily comprehensible as both "go" and "up" imply increase and rise, while “up” distinctly signifies upward movement in conjunction with the verb "go." They contend that compositional structures enhance language acquisition and should be introduced as an initial step in teaching phrasal verbs. However, the challenging aspect arises when particles alter their meanings or become fixed in the contribution of meanings. The dependence of meanings on how they are utilized poses a significant challenge for second language learners. For instance, the phrasal verb “run out” in the context of cricket and “run out of stock” in corporate affairs are entirely context-dependent. Schmitt ( 2014 ) has also noted that second language learners frequently struggle to distinguish between fixed and semi-fixed multiword expressions, particularly within a specific context. For these learners, grasping the fixed nature of particles is more challenging because, in fixed expressions such as idiomatic phrases, the constituent parts do not retain their core meanings. This poses problems for L2 learners when an entirely different and unfamiliar use in a particular context suggests different implications altogether. This implies that frozen expressions pose a significant challenge for L2 learners because of their fixed meanings. Without compositionality, L2 learners must rely on their native language and infer meanings through context and translation, which raises questions about the usefulness and accuracy of these methods (Cornell, 1985 ; Sinclair & Renouf, 1988 ; Sinclair, 1991 ). For fixed expressions, translation is not effective and may result in various unintended meanings in the target language. Subsequently, L2 learners fail to comprehend verbal expressions employing phrasal verbs without knowing what they refer to. We contend that the integration of frozen expressions into educational curricula is imperative. This methodology is crucial for contextualized learning and offers a viable pathway for second language learners to acquire typical fixed expressions without requiring an in-depth understanding of specific terminology. Nonetheless, this endeavor presents considerable challenges. Such a perspective is corroborated by Tono (2012), who asserts that L2 learners encounter substantial difficulties in understanding these fixed expressions. Biber et al. ( 1999 ) identify it as a key reason why phrasal verbs are not included in initial teaching materials, which creates extra challenges for intermediate and advanced learners when they encounter these constructions for the first time at their respective proficiency levels. This may explain why individuals rarely use phrasal verbs in their daily interactions, ultimately limiting the proficiency of second language learners. As previous research (Lightbown & Spada, 1990 ; Spada, 1997 ) shows, second language learners tend to focus more on form and grammar. Simultaneously, phrasal verbs frequently evade this form-meaning conceptualization, thereby rendering them more challenging to acquire. For instance, the verb "bring" is straightforward and is typically understood by intermediate learners; however, when it is employed as “bring up," “bring in," and “bring about," the meanings of "bring" are no longer consistent. In light of this, Schmitt (2018) suggests the contextual use of phrasal verbs, which can help learners understand them more effectively, particularly through the use of multimedia and interactive exercises. He believes that corpus analysis, particularly in terms of frequency and concordances, significantly aids learners in using phrasal verbs correctly. The duality exhibited by particles in Phrasal Verb constructions serves either as a directional indicator or as an idiomatic element (Biber et al., 1999 ). During the process of grammaticalization, as Hopper and Traugott ( 2003 ) suggest, their original meanings are either completely replaced or partially changed with idiomatic or more abstract senses. For similar reasons, Darwin and Gray ( 1999 ) regard PVs, once lexicalized, as a challenging task for second language learners. Gardner and Davies ( 2007 ) further confirm that second language learners avoid PVs due to this duality, resulting in either unpredictability or idiomatic opacity. To sum up, Phrasal verbs (PVs) are complex for second language learners due to their idiomatic and syntactic features, often leading learners to avoid them. Despite extensive research on their structure (Biber et al., 1999 ; Celce-Murcia & Larsen-Freeman, 1999 ; Gardener & Davies, 2007; Liu, 2011 ; Schmitt, 2014 ; Mahpeykar & Tyler, 2015 ), the functions of particles, especially directional adverbials like “out,” “up,” and “down”, remain underexplored in academic writing. This study aims to address this gap by utilizing BAWE preloaded in Sketch Engine (Kilgarriff et al., 2014 ), with a focus on directional particles across different genres. Mastery challenges include semantic opacity, varying frequency, fixedness, register sensitivity, and genre-specific use, such as in methodology sections versus essays. The study responds to key research questions: How do adverbial particles “out,” “up,” and “down” operate in academic phrasal verb constructions, either through their composition or idiomatic meanings? What are the frequency and distribution patterns of these PVs across genres in the BAWE corpus? What pedagogical and linguistic implications do these patterns have for second language learners? LITERATURE REVIEW As established in the preceding section, Phrasal Verbs (PVs) continue to present considerable challenges for second language (L2) learners due to their ambiguous meanings, flexible syntactic structures, and context-dependent idiomatic usage (Gardner and Davies, 2007 ; Schmitt, 2014 ; Alangari et al., 2020 ). Unlike single-word verbs, PVs comprise a verb combined with one or more particles, forming multiword expressions that can range from entirely literal to highly idiomatic meanings. This variation complicates the learning process, particularly when their meanings cannot be inferred from individual components. These characteristics not only create lexical difficulties but also pose pragmatic and functional challenges, especially within academic writing. A key linguistic challenge in learning phrasal verbs (PVs) is their varying degree of idiomaticity. Researchers such as Celce-Murcia and Larsen-Freeman ( 1999 ) and Liu ( 2011 ) describe PVs as existing on a continuum, ranging from transparent phrases like "go down the stairs" to fixed idiomatic expressions like "point out flaws," which often defy literal interpretation. Learners rely heavily on memorization and context, unlike more compositional PVs, which can be understood by analyzing their meanings. Zamin et al. ( 2019 ) classify particles as either compositional, adding spatial sense, or frozen, part of fixed idioms. Hybrid forms, such as "go up" and "take off," blur these categories. L2 learners often avoid phrasal verbs (PVs), replacing them with more formal Latinate verbs (Thornbury, 2002 and 2017 ; Liao & Fukuya, 2004 ; Schmitt, 2014 ; Haugh & Takeuchi, 2022 ). For example, 'conduct an experiment' is frequently used instead of 'carry out an experiment,' even though the latter sounds more natural in academic contexts. Such substitutions may reflect caution but reduce expressive variety and limit the use of common academic English expressions (Schmitt & Schmitt, 2020 ). Learners' avoidance is also influenced by their first language (L1). Speakers of languages with few particles (e.g., Chinese) tend to use PVs less often. In contrast, speakers of particle-rich languages (e.g., German) often overuse PV structures based on their native syntax (Kamarudin, 2013 ). Wei ( 2021 ) has meaningfully shown that learners with higher proficiency use significantly more PVs. Initial research (Biber et al., 1999 ) studied how often phrasal verbs appear in different textual genres but offered limited understanding of how genre affects the semantic meaning of particles. Most studies mainly look at particle occurrence rates and often overlook how genre influences whether PVS are idiomatic or compositional. For example, "set up" in scientific texts usually works procedurally, while in philosophical essays, it often refers to a theoretical idea. This study aims to explore how directional particles (out, up, down) change their meanings and usage across various academic genres, focusing not just on frequency but also on how genre-specific patterns shape their interpretation. Directional particles have experienced diachronic delexicalization, whereby their original spatial meanings have become increasingly abstract over time (Hopper & Traugott, 2003 ). This process of grammaticalization is particularly observable in academic writing, where the behavior of particles varies according to genre. In scientific disciplines, particles such as "down" generally maintain literal, procedural meanings, exemplified by their use in breaking down compounds, which corresponds with the demand for precision in language (Biber et al., 1999 ; Darwin & Gray, 1999 ; Baldwin & Villavicencio, 2002 ; Baldwin et al., 2003 ). Conversely, texts within the humanities frequently adopt particles as rhetorical idioms, exemplified by phrases such as "sum up arguments" or "point out flaws," utilized for evaluative purposes (Gardner & Davies, 2007 ; Biber & Jones, 2009 ; Paquot, 2010 ). Additionally, the particle "up" functions as a semantic pivot, oscillating between literal uses (e.g., "build up pressure") and figurative uses (e.g., "build up a theory"), with these functions being influenced by genre and context (Lindner, 1981 ). This variation reveals a more profound theoretical divide: cognitive models, such as those proposed by Lindner ( 1981 ), concentrate on image schemas to elucidate the spatial and metaphorical meanings of particles, whereas corpus methodologies (e.g., Gardner and Davies, 2007 ) analyze distributional data. This research integrates these perspectives by employing Goldberg's (2006) Construction Grammar, which interprets PVs as genre-specific constructions influenced by disciplinary standards and communication objectives, thereby providing an explanation for grammaticalization and idiomaticity within genres. Prior studies have predominantly neglected the significance of directional particles in academic language, instead concentrating on aspectual particles such as ‘off’ and ‘through’, without developing comprehensive models for directional particles across various genres (Liu, 2011 ; Siyanova-Chanturia & Martinez, 2015 ). Despite their increasing prominence, constructionist grammar and phraseology theories remain underutilized in genre-specific corpus analysis. This study addresses this gap by examining 'out', 'up', and 'down' within academic genres in the BAWE corpus, offering valuable insights and pedagogical recommendations. The tools of corpus linguistics are vital for the analysis of PVs, notwithstanding certain limitations. Researchers frequently reference various frequency thresholds, ranging from 5 to 40 hits per million. In this investigation, we employ five hits to identify pertinent and occasionally infrequent academic PVs. Due to the variability in idiomaticity coding, our methodology encompasses semantic, syntactic, and contextual analyses to ensure accuracy. Extensive corpora, such as the BNC and COCA, afford a comprehensive overview of language utilization but may obscure register boundaries. Conversely, BAWE provides distinct disciplinary categories, thereby facilitating genre classification. Research has indicated particular challenges in language teaching methodologies. Many conventional resources depend on isolated PV lists (Cornell, 1985 ), predominantly emphasizing compositional meanings, despite the fact that academic language is abundant in idioms (Schmitt, 2014 ). Strategies involving L1 transfer are infrequently employed, potentially diminishing their effectiveness (Jiang, 2004 ). Although approaches such as corpus-based examples (Gardner & Davies, 2007 ), multimedia contextualization (Schmitt & Schmitt, 2020 ), and formulaic instruction (Wray, 2002 ) are available, they have not been systematically organized according to grammatical complexity. This study proposes a novel model that advances from basic (compositional) to hybrid, and ultimately to idiomatic, in accordance with various genre functions. This study introduces a Genre-Construction Interface Model that combines corpus linguistics, Construction Grammar, and teaching strategies, drawing on Goldberg’s ( 2006 ) form-meaning pairs and Hopper and Traugott’s ( 2003 ) paths of grammaticalization. It positions directional particles along a spectrum of phraseological units to illustrate features like semantic bleaching and genre-specific variations. The research applies Construction Grammar to directional particles within academic discourse, addressing issues related to frequency, function, idiomaticity, and compositionality. It addresses four key gaps: providing quantitative data on genre-particle interactions, focusing on neglected directional particles, developing genre-aware teaching methods for L1 language types, and integrating cognitive and corpus-based approaches. It redefines directional particles as vital, genre-specific skills for enhancing academic literacy in English as a second or foreign language. METHODOLOGY This study used a mixed-methods corpus linguistic approach to examine the duality of adverbial particles (out, up, down) in academic phrasal verbs. It combined quantitative corpus analysis with qualitative contextual analysis, following established protocols (Gardner & Davies, 2007 ). The BAWE corpus, representing authentic academic writing across disciplines and proficiency levels (Heuboeck et al., 2008 ; Hyland, 2008 ), contains 6.5069 million words and over 3000 texts across four proficiency levels and 34 disciplines in four major fields. Table 1 BAWE Categorization into Major Fields Field % Corpus Genres Included Arts and Humanities 32% Essays, critiques Social Sciences 28% Case studies, proposals Life Sciences 24% Methodology recounts Physical Sciences 16% Explanations, design specs The data was extracted from the Sketch Engine (Kilgarriff et al., 2014 ) using Corpus Query Language (CQL) with the pattern: [word="out" | word="up" | word="down" and tag="RP"] [lemma="."] [tag="VB."] {0,6} and [word="down" and tag="RP"] [!tag="BE"]. The parameter captures 0–6 tokens between a verb and a particle, limited to adverbial particles, excluding the be + particle construction with !tag="be". Further exclusion criteria are provided below. Table 2 Exclusion criteria for directional particles Category Included Excluded % Excluded Syntactic Verb + particle constructions Prepositional uses 18.7% Semantic Directional particles Aspectual particles (e.g., finish up ) 12.3% Functional PVs with lexical verbs Copular constructions 15.2% Our criteria are founded upon established best practices within the field of corpus linguistics. Research in this area exhibits variation in the thresholds set for lexical significance, which are contingent upon the specific type of corpus and overarching research objectives. Hunston ( 2002 ) recommends a minimum of 40 hits per million words to ensure reliability. Bestgen ( 2018 ) suggests a range of 10 to 40 hits, depending on contextual factors. O'Keeffe et al. (2007) advise a threshold of 4 hits per million, while also stipulating a minimum of 40 raw hits for validity. These criteria are adjusted to maintain an appropriate balance between accuracy and relevance. For the purposes of this study, five hits per million and 40 raw hits are employed for academic PVS. To define idiomaticity in phrasal verbs, a semantic classification was employed, evaluating compositionality, replaceability, object abstractness, and fixedness. This approach ensured a consistent classification of idiomatic versus literal usages. The reliability metrics encompass Cohen's κ, which is .89, signifying near-perfect agreement. Discrepancies were resolved through consensus, and a 95% confidence interval for accuracy was established at ± 2.1%. Frequency profiling with normalized counts per million words. Genre distribution mapped using chi-squared tests and binomial logistic regression: logit (Idiomatic) = β₀ + β₁(Genre) + β₂(Discipline) + β₃(Particle). Qualitative Analytical Procedure We have analyzed concordance lines by academic purpose, including procedures, critiques, and essays, and subsequently validated the statistics. Fisher's Exact Test was employed for low-frequency PVs (p < 0.05), complemented by bootstrap resampling (1,000 iterations) to determine confidence intervals. The Sketch Engine enables the comparison of four academic genres for each particle and phrasal verb, encompassing frequency and density. These limitations were mitigated through rigorous statistical validation. Table 3 Data Validation through Mitigation Strategies Limitation Mitigation Strategy Validation Outcome Limited particle scope Explicit focus on high-frequency directional particles Fisher's test confirmed representativeness (p = .018) BAWE excludes spoken data Compared with the BASE corpus samples 92% consistency in PV patterns Threshold arbitrariness Fisher's Exact Test validation All thresholds are significant (p 89% of pedagogically relevant PVs while maintaining statistical robustness (CI: 86.7–91.3%)." RESULTS AND DISCUSSION This section presents a triangulated analysis addressing the study's three research questions through an integrated quantitative, qualitative, and statistical perspective. Building on Construction Grammar principles (Goldberg, 2006 ) and frameworks of idiomaticity (Siyanova-Chanturia & Martinez, 2015 ), we demonstrate how academic genres influence particle semantics, with direct implications for L2 teaching. Overall Distribution and Semantic Duality (RQ1) A total of 9,866 phrasal verb (PV) constructions with target particles were extracted from BAWE (see Table 1 ). Importantly, 78.25% showed idiomatic meanings, supporting Schmitt and Schmitt's (2020) avoidance hypothesis. Table 4 Particle Distribution in Academic PVs Particle Frequency Frozen % Compositional % χ² (vs. BNC) Out 4836 98.40 1.60 892.4 Up 3804 64.29 35.71 328.7 Down 1226 36.80 63.20 167.2 >p < .001; BNC reference: Gardner and Davies ( 2007 ) The extreme χ² values (e.g., χ² = 892.4, p < .001 for 'out'; Cramer’s V = 0.42) demonstrate that academic PVs occur 5.7 times more densely than in general English. Similarly, the influence of 'up' (χ² = 328.7, p < .001; V = 0.25) and 'down' (χ² = 167.2, p < .001; V = 0.18) exhibit strong effect sizes, emphasizing the significance of these associations. Cramer’s V was calculated as: V = χ²/n×(k − 1), where n = 9,866 and k = 2. Effect sizes are consistent with Cohen’s benchmarks (V = 0.1: small; 0.3: medium; 0.5: large). Binomial regression indicates that particle type predicts idiomaticity (β = 2.17, SE = 0.18, p < .001), with "out" being 84.7 times more likely than "down" to be idiomatic (OR = 84.7, CI: 76.2–94.1). This supports grammaticalization pathways (Hopper and Traugott, 2003 ), suggesting near-complete semantic bleaching of “out” in “carry out,” whereas “down” remains associated in “break down,” and “up" holds an intermediate position. Functional Distribution of "Out" PVs Given that the study focuses on the compositional and frozen characteristics, phrasal verbs are evaluated based on their frequency, structure, and semantic features. Analyzing all phrasal verbs within a single article proves challenging; therefore, only the top ten are discussed comprehensively, followed by an examination of the duality of adverbial particles. Utilizing the preloaded BAWE corpus in Sketch Engine and Corpus Query Language, we identified a total of 8,239 phrasal verbs. The data indicates that “carry out" is the most prevalent in the BAWE corpus, constituting 29.50% of phrasal verb usage, with 6,469 occurrences and 4,836 instances with verbs. Excluding “be” forms and low-frequency collocations, "out" emerges as the most common adverbial particle at 57%, frequently paired with verbs. Those with over 40 occurrences and five relative hits are listed below. Table 5 Frequencies and percentages of phrasal verbs with particle “out” PV Frequency Reltv. Freq. % from of PVs carry out 1554 186.41 29.50 point out 795 95.36 15.09 find out 283 33.94 5.37 set out 228 27.35 4.32 work out 164 19.67 3.11 turn out 102 12.23 1.93 rule out 89 10.67 1.68 lay out 61 7.31 1.15 stand out 61 7.31 1.15 go out 48 5.75 0.91 come out 45 5.39 0.85 Total 3430 411.45 65.12 The phrasal verb "carry out” constitutes over 30% of instances involving particles with lexical verbs, amounting to 1,554 occurrences. It is predominantly found in essays (191), critiques (171), and design specifications (57), underscoring its significance in formal contexts. All occurrences are established fixed expressions devoid of compositional meaning. While idiomatic usages are prevalent, their interpretations are neither transparent nor adaptable. The object types tend to be abstract, and substituting words with synonyms does not necessarily retain the original meaning, thereby highlighting the critical role of context for precise comprehension. The phrasal verb "point out" accounts for 15% of usage, totaling 795 instances. Contextual analysis reveals its primary appearance in non-literal contexts, with subsequent frequent usage in that-clauses (411), constructions involving "the” and abstract nouns (288), or abstract nouns alone. This supports the observation of its fixed usage within the BAWE corpus. A comparable analysis of “find out” indicates its greater prevalence in essays (31), methodology recounts (24), critiques (19), and problem questions (19). Collectively, "carry out," "point out," and "find out" represent over fifty percent of related phrasal verbs, which are predominantly employed in analytical, critical, investigative, and argumentative academic writing. These idiomatic phrasal verbs with “out" generally do not significantly alter their fundamental meanings in academic writing. For instance, “go out” and “work out" demonstrate that "out” sometimes contributes to the meaning while other times functions idiomatically. “Go out” predominantly employs "out" as a particle, analogous to 'going out to work.' It is often followed by words such as "to,” “with,” “and,” or “on,” with only nine out of forty-eight occurrences being idiomatic. Conversely, “come out” is primarily idiomatic, manifesting 29 times out of 45. “Set out” is chiefly idiomatic in scholarly essays to denote aiming to achieve, used 67 times, frequently with phrases like “set out to accomplish,” or following “the” and “in” with abstract nouns. These patterns indicate that these phrases are predominantly non-literal and can often be employed unchanged. Similar patterns are observed with “turn out,” “stand out,” and “rule out,” which are also frequently idiomatic. Table 5 Top PVs with Particle “Out” with their academic functions and Genre Ratio PV Idiomatic % Academic Function Genre Ratio Carry Out 100 Research Processes Methodology: 8.3 Point out 99.7 Identifying limitations Critique: 12.1 Find out 100 Reporting discoveries Essay: 6.7 Set Out 98.2 Stating Objects Proposal: 9.4 The findings may help L2 learners utilize phrasal verbs effectively in academic domains. Functional Distribution of “up” in the BAWE Corpus The BAWE corpus documents 12,528 instances of the word "up," with 4,216 instances functioning as particles within phrasal verbs, at a frequency of 505 per million (0.051%). "Up" ranks as the second most frequent particle associated with lexical verbs in English academic writing. The subsequent phrasal verbs satisfy the criteria established for this study. Table 6 Phrasal Verbs with Particle “up” in the BAWE Corpus Lemma Frequency Rltv. Freq. % of PVs set up 561 67.29 4.45 make up 404 48.46 3.21 build up 252 30.22 2.00 pick up 174 20.87 1.38 take up 151 18.11 1.20 come up 147 17.63 1.16 end up 141 16.91 1.12 sum up 139 16.67 1.10 open up 103 12.35 0.81 give up 102 12.23 0.81 back up 99 11.87 0.78 bring up 79 9.47 0.62 catch up 70 8.39 0.55 grow up 65 7.79 0.51 speed up 61 7.31 0.48 go up 51 6.11 0.40 follow up 48 5.75 0.38 break up 45 5.39 0.35 draw up 45 5.39 0.35 stand up 42 5.03 0.33 keep up 41 4.91 0.32 Total 2820 338.28 22.41 The table indicates that “set up” is the most prevalent phrasal verb (PV) with the particle “up” in this list, followed by “make up” and “build up,” which collectively account for over 10% of all instances of “up” in the concordance. Most occurrences demonstrate their idiomatic and constructive uses. They typically refer to processes such as establishing experiments, actions like installing instruments, and adjustments such as arranging a camera, among others. Below are the concordance lines selected at random for “up.” The two most prevalent phrasal verbs associated with construction are 'set up' and 'make up.' 'Set up' appears 561 times across the corpus, predominantly within essays, case studies, critiques, and methodology sections, thereby signifying its prominence within the scientific domain. It is employed to describe experiments, research designs, and practical applications, with 46 of the 111 occurrences involving 'up' as an inseparable particle, frequently pertaining to plans or equipment. Approximately 41% of these instances are idiomatic, while 59% are literal, underscoring its relevance to academic and process-oriented writing rather than the humanities or social sciences. Conversely, 'make up' is encountered 404 times in diverse contexts, notably in essays (188 occurrences), often within argumentative, analytical, or descriptive compositions. Its moderate utilization in methodology (63 instances) and explanatory sections (57 instances) indicates their role in facilitating clarity and structural coherence. The phrasal verb "make up" is seldom employed in formal writing, such as design specifications, proposals, and research reports, primarily for descriptive purposes within the soft sciences. Conversely, the phrasal verb "Build up" is prevalent, with over 30 occurrences per million tokens, particularly in essays (89 instances), critiques (29), case studies (29), and other texts. "Pick up" appears 174 times, chiefly in essays (63), design specifications (22), and critiques (21). "Take up” occurs 151 times, predominantly in essays (72), as well as in explanatory texts and case studies. "Come up" is found 151 times, mainly in essays (51), and also in narratives and critiques. "End up" appears 141 times, primarily in essays (93), followed by critiques. "Sum up” occurs 139 times, mainly in essays (90), with some instances in critiques and explanatory texts. Most "up"-phrasal verbs are common in essays, especially those of argumentative and analytical nature, demonstrating discursive use, tone, and roles; they are more prevalent in the humanities than in the sciences. Further research is required to distinguish between formal and informal usages. The functions of these phrasal verbs include "sum up” in conclusions, “end up” for unintended consequences, and “take up" at the beginning of discussions. Even less frequent verbs such as "give up" and “back up" serve important broader functions. In academic writing, "up" often marks procedures, descriptions, and processes, with meanings that are both variable and fixed. For example, "end up" frequently indicates outcomes with a negative connotation, "give up” signifies abandonment, and "break up” is used to describe political divisions. Table 7 The PVs with “Up” across Genre PV Idiomatic % % in sciences % in Humanistic ΔGenre (p) Set up 40.8 78.3 22.1 < .001 Make up 10.4 5.2 93.7 < .001 Build up 42.9 18.6 86.3 < .001 End up 100 100 100 - The Hybrid Semantics of "Up' demonstrates a balanced duality in genre determination. Literal patterns encompass methodological dominance within the field of physics and idiomatic preferences prevalent in the humanities. Aspectual phrasal verbs (e.g., "end up," "sum up") are consistently fixed, corroborating the aspectual category proposed by Celce-Murcia and Larsen-Freeman ( 1999 ). The BAWE corpus contains numerous compositional phrasal verbs, linking 'up' to meanings such as direction; for example, 'build up' can be partly compositional ('built up from basic principles') or metaphorical ('build up tensions'). 'Go up' is employed both literally and metaphorically ('prices went up'). 'Speed up' and 'stand up' are fully compositional. Some flexible phrasal verbs, such as 'set up,' 'take up,' and 'make up," are frequently used in both literal and idiomatic contexts. Methodological approaches and case studies often utilize compositional phrasal verbs, e.g., 'setting up the apparatus,' whereas academic essays tend to favor idiomatic expressions like 'summing up the argument.' Critiques and proposals exhibit mixed usage, e.g., 'taking up a position' and 'building up evidence.' In scientific discourse, compositional phrasal verbs are predominantly employed in introductions and methods sections, whereas idiomatic phrasal verbs predominate in discussions and conclusions. Functional Distribution of ‘down” in the BAWE Corpus The particle “Down” is documented 1799 instances within the BAWE corpus, corresponding to a relative frequency of 255. Within phrasal verbs, it occurs 1307 times, serving as a conventional adverbial particle with multiple functions. It is incorporated into 146 phrasal verbs, with an average incidence of 155 instances per million, although only six surpass the threshold of 40 occurrences and 5 per million. Table 8 Phrasal Verbs with Particle “down” in the BAWE Corpus PV Frequency Rltv. Freq. % of PVs break down 247 29.62959 5.03568 slow down 95 11.39599 1.9368 lay down 86 10.31637 1.75331 go down 49 5.63802 0.95821 cut down 42 5.03823 0.85627 Total 519 62.0182 10.54027 The phrasal verb “break down” is employed 247 times, corresponding to a frequency of 29.62 per million. Although it is less prevalent than “carry out” or “set up,” it maintains significant importance. Its primary occurrence is within essays (90 instances), comprising 90% of its usage, which suggests it is less confined to specific genres. Additionally, it appears in the methodology section (40), critique (29), explanation (24), and case studies (14), predominantly as a frozen particle with verbs. Its density is comparatively higher in other genres than in essays, and it sometimes combines with verbs to preserve meaning. Although this phrasal verb frequently appears in academic writing alongside a compositional partner, it is also widely utilized within the soft sciences and humanities, often with a frozen particle as in “breaking down the entire framework of society.” This phrasal verb pertains to societal disintegration and emotional collapse, a term more frequently employed within abstract disciplines rather than scientific domains. It underscores the technical and metaphorical utilization of “break down” in scholarly discussions, serving functions in explanations, evaluations, deconstruction, and argumentation based on particle application. The phrasal verb 'slow down' possesses literal meanings in everyday contexts and more nuanced interpretations when used as a fixed particle. With a total of 95 occurrences, it is most commonly found in methodology sections (28 instances), followed by essays (21 instances), and research reports (12 instances). Genres such as critiques, case studies, and explanations generally feature fewer than ten examples. An illustrative example from a methodology source demonstrates typical usage, such as “slowing down” the pace or processes. However, at the same time, we have instances where it shows partial compositionality and leans more toward idiomatic use, such as “slowing down of the growth in the Retardation phase”. The concordances demonstrate that the phrase "slow down” primarily functions in descriptive contexts and causal analysis, particularly within the hard sciences. The phrasal verb “lay down” appears 86 times, predominantly in Essays (39 occurrences, with a density of 94.34%) and Critiques (15 occurrences), indicating its typical usage. The particle “down” infrequently serves a compositional purpose; for instance, in "the dogs lay down” within Essays. Conversely, in critiques, the expression “laying down the criteria” generally possesses an idiomatic and conventional significance. This Phrasal Verb is predominantly observed within the disciplines of social sciences and humanities, fulfilling roles such as delineating theories and establishing legal frameworks. The final two instances, both containing the word "down," are “go down" (46 occurrences) and “cut down" (42 occurrences). "Go down” is seldom employed outside of idiomatic contexts in academic dialogue, with only 14 appearances in essays, predominantly accompanied by fewer than ten concordance lines. Its usage is more prevalent in methodological recapitulations, with an approximate increase of 225%, although it appears more frequently in essays, such as in expressions like "economies going down." It is primarily utilized to analyze trends and changes over time. Similarly, “cut down” demonstrates moderate usage as a component of the particle and is frequently found in idiomatic contexts. It appears 14 times in essays and 12 times in case studies. The relative frequency in essays (69%) suggests it is not characteristic of this corpus type, whereas the density in case studies (366%) indicates that this PV is standard in such texts. This PV appears in policy suggestions, reduction, and environmental impacts, aligning more with hard sciences than the humanities. The concordance lines indicate that most instances are used metaphorically in an abstract sense to preserve figurative accuracy within academic contexts. They serve various academic functions, including explaining, trend analysis, evaluation, and making recommendations. Some genres also emphasize particular usages, such as idiomatic expressions in essays and explanatory functions in hard sciences. The compositional tendencies of this particle differ from others by maintaining stronger spatial semantics, as shown in the table. Table 9 Semantic Flexibility of "Down" PVs PV Compositional Instances (%) Literal Meaning Figurative Extension Break down 60.3 Mechanical failure Conceptual analysis Slow down 31.6 Mechanical Economic decline Go down 51.6 Reduced velocity Numerical reduction Cut down 78.6 Physical reduction Resource conservation Regression analysis has established that the Life Sciences exhibit 73.4% literal utilizations, in comparison to 62.2% idiomatic utilizations within the Social Sciences. Genre-Driven Variation Patterns (RQ2) Genre emerged as the most significant predictor of particle semantics (β = 1.84, SE = .23, p < .001), accounting for 38.7% of the variance in idiomaticity (R²=.387). Humanities genres demonstrated an idiomatic density 2.3 times greater than that of the sciences. Table 10 Genre-Mediated Particle Functions Genre Idiomatic PVs (%) Frequent Compositional PVs Frequent Idiomatic Disciplinary Bias Essay 84.2 Go down (63%) Carry Out (99.7%) Humanities: 5.2 Critique 79.6 Set up (41%) Point out (98.7%) Social Sciences: 3.1 Methodology 52.3 Break down (68%) Rule out (96.4%) Physical Sciences: Ref Case study 61.7 Slow down (62%) Find Out (97.2%) Life Sciences:1.8 >p < .001, p < .01, p < .05; OR = Odds Ratio for idiomaticity vs. Physical Sciences Argumentative PVs constitute 92.3% of idiomatic particle usage in essays within the humanities discipline. Abstract object constructions, such as “point out” flaws, exceed 99% (f = 795), and “laid down” is entirely idiomatic (f = 86). A notable binomial regression indicates variation in construction patterns involving verb + out + abstract noun, with χ² = 213.4, p < .001. The section on scientific methodology exhibits 68.5% of compositional particles accompanied by procedural PVs, including ‘set up apparatus’ (59.1%) and ‘break down samples’ (67.9%), observed as particle + concrete noun (φ = .73, p < .001). Examining the particle-specific semantic landscape, it can be asserted that with 98.4% idiomatic uses, “out” establishes its dominance in academic discourse, indicating complete semantic bleaching. Pedagogical Implications (RQ3) Our third research question on pedagogical implications outlines a way forward. The analysis yields three evidence-based pedagogical imperatives. First, PVs are genre sensitive and require targeted instruction. For example, methodology PVs like 'set up' are less common in critiques focusing on idiomatic expressions such as ‘point out' or 'sum up'. We also argue that genre-specific uses should be included in learning materials in contrastive contexts, like “set up the spectrometer” in Chemistry and “set up a theoretical framework” in Sociology. The third point emphasizes construction-based sequencing, where pedagogically, compositional prototypes are introduced first. Literal to figurative uses should be integrated into the material per Johnson’s (1987) classification. Figure 4: Pedagogical preferences suggested by Johnson (1987) Similarly, second language instruction should incorporate idiomatic clusters. Phrasal Verbs (PVs) can be classified as analytical (e.g., point out, rule out) and procedural (e.g., set up, break down). Corpus analysis reveals patterns such as ‘conducting experiments’ that offer alternatives, thereby supporting Schmit’s (2018) PV avoidance hypothesis; however, classroom validation remains necessary. Additionally, findings suggest enhancements to existing models. We propose a Phraseological Spectrum Model (PSM), founded on Sinclair’s ( 1991 ) Idiom Principle, Howarth’s (1998) Spectrum, Wray’s ( 2002 ) Formulaic Language Theory, and Granger and Paquot’s ( 2008 ) Academic Phraseology Framework. Academic phrasal verbs also constitute genre-specific constructions, such as: Construction / Pattern: [Verb + Particle] GENRE = SEMANTIC_PROFILE Example [SET + UP] Methodology = Procedural action These advances address the limitations in Gardner and Davies' (2007) frequency-based approach by integrating semantic and contextual aspects. The findings support the conclusion by showing how genre patterns from corpora can reshape phrasal verb teaching and enhance phraseological theory. The analysis connects Biber et al.'s ( 1999 ) lexical framework with constructionist methods, providing a cohesive explanation of academic PV semantics. CONCLUSION This study investigates the role of directional particles (out, up, and down) in academic phrasal verbs, providing three key insights with substantial implications. It demonstrates that 78.25% of their utilization is idiomatic, with ‘out’ entirely idiomatic (98.4%), ‘up’ partially idiomatic (64.3%), and ‘down’ predominantly literal (63.2%). This gradient aligns with grammaticalization theory, wherein spatial meanings diminish to develop abstract, genre-specific functions. Genre serves as the primary predictor of particle semantics, accounting for 38.7% of the variation in idiomatic usage (β = 1.84, p < .001). Humanities genres exhibit more than double the idiomatic density of scientific genres, with essays at 84.2% compared to 52.3% in methodological sections. Construction patterns vary: humanities tend to favor verb + particle + abstract noun (e.g., point out limitations), whereas scientific writing prefers particle + concrete noun (e.g., break down samples). These findings illustrate that academic genres significantly influence rhetorical objectives and the employment of particles within phrasal verbs. The research has demonstrated that directional particles within academic discourse are genre-specific constructions rather than merely freely combinable words. This observation necessitates a reevaluation of phrasal verbs within the framework of Construction Grammar (Goldberg, 2006 ), where form-meaning pairings exhibit variation across different genres. For instance, “SET UP” in methodological contexts signifies procedure, whereas in the humanities, it denotes abstract frameworks. This insight clarifies the ongoing debate concerning idiom compositionality and highlights the significance of recurring particle patterns in scholarly language. Pedagogically, the findings suggest three priorities. First, instruction should focus on genre-specific sequencing: learners need to learn compositional PVs common in scientific language (like "set up" or "break down") before idiomatic clusters in the humanities (such as "point out" or "lay down"). Second, teachers should use construction-based scaffolding, such as visual aids like image schemas (Johnson, 1987), to help students grasp literal-figurative shifts (e.g., from "go down stairs" to "prices go down"). Third, the research recommends L1-sensitive strategies, including creating contrastive exercises for speakers of particle-rich languages and activities to reduce avoidance in particle-poor languages. This research provides both theoretical and pedagogical contributions; however, it also exhibits certain limitations. It depends on the BAWE corpus, focusing solely on written academic English, thereby excluding spoken registers. Future research should incorporate the BASE corpus for comparative analysis and investigate less frequent aspectual particles, such as 'off' or 'through', across various disciplines to attain a more comprehensive understanding of phrasal verb usage. Furthermore, subsequent studies might explore how learners internalize genre-particle constraints over time, employ computational models for genre-aware phrasal verb recommendations, and compare grammaticalization pathways among English learners from different L1 backgrounds to evaluate the influence of L1 on PV acquisition. Overall, this study demonstrates that adverbial particles in academic writing constitute a genre-mediated spectrum shaped by discipline-specific conventions. By employing corpus-based, genre-sensitive methodologies, educators can redefine phrasal verbs from potential obstacles into rhetorical instruments that enhance scholarly and disciplinary fluency. Declarations Ethics and Consent to Publish declarations Not Applicable. Author Contribution 1. T. Q. Conceptualized, wrote the main manuscript, and curated data.2. A. T. formatted the manuscript and researched previous studies.3. S.K. provided overall supervision and helped with the technicalities. 4. N.H. reviewed the manuscript and suggested the changes.5. S. A. A. G. assisted in data collection for the paper.6. I.A.S. proofread and provided feedback. Acknowledgement We have used Grammarly, a software designed to enhance language clarity and precision. However, it has been carefully reviewed to ensure that the core idea remains unchanged. Data Availability We have utilized the British Academic Written English (BAWE) corpus, preloaded in the Sketch Engine (Kilgarriff et al., 2014), and it is accessible through the built-in interface of the Sketch Engine. It is freely available for subscribers at: https://app.sketchengine.eu/#dashboard?corpname=preloaded%2Fbawe2 References Alangari, M., Jaworska, S., & Laws, J. (2020). Who’s afraid of phrasal verbs? The use of phrasal verbs in expert academic writing in the discipline of linguistics. Journal of English for Academic Purposes, 43 , 100814. https://doi.org/10.1016/j.jeap.2019.100814 Baldwin, T., Bannard, C., Tanaka, T., & Widdows, D. (2003). An empirical model of multiword expression decomposability. In Proceedings of the ACL 2003 Workshop on Multiword Expressions: Analysis, Acquisition and Treatment (pp. 89–96). Association for Computational Linguistics. https://doi.org/10.3115/1119282.1119294 Baldwin, T., & Villavicencio, A. (2002). Extracting the unextractable: A case study on verb-particles. In D. Roth & A. van den Bosch (Eds.), Proceedings of the 6th Conference on Natural Language Learning (CoNLL-2002) – Volume 20 (pp. 1–7). 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Form-focused instruction and second language acquisition: A review of classroom and laboratory research. Language Teaching, 30 (2), 73–87. https://doi.org/10.1017/S0261444800012799 Thornbury, S. (2002). How to teach vocabulary . Longman. Thornbury, S. (2017). Prepositions and phrasal verbs. In About language: Tasks for teachers of English (pp. 172–180). Cambridge University Press. https://doi.org/10.1017/9781009024525.029 Wei, Y. (2021). Use of English phrasal verbs of Chinese students across proficiency levels: A corpus-based analysis. International Journal of TESOL Studies, 3 (4), 25–41. https://doi.org/10.46451/ijts.2021.12.03 Wray, A. (2002). Formulaic language and the lexicon . Cambridge University Press. Zamin, A. A., Elfeky, M., Kamarudin, R., & Majid, F. A. (2019). A corpus-based study on the use of phrasal verbs in Malaysian secondary school textbooks. International Journal of Applied Linguistics and English Literature, 8 (6), 76–84. https://doi.org/10.7575/aiac.ijalel.v.8n.6p.76 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7222728","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":493452056,"identity":"74207d66-b1d2-4b63-8231-a64fa5a8cd05","order_by":0,"name":"Tahir 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Amir","lastName":"Gardazi","suffix":""},{"id":493452065,"identity":"094ae034-3313-49c5-a849-1755605a9baf","order_by":5,"name":"Iftikhar Ahmed Shaheen","email":"","orcid":"","institution":"Majmaah University","correspondingAuthor":false,"prefix":"","firstName":"Iftikhar","middleName":"Ahmed","lastName":"Shaheen","suffix":""}],"badges":[],"createdAt":"2025-07-26 18:08:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7222728/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7222728/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88855410,"identity":"0fa637e6-f72a-4c0e-994a-3daab5c05edf","added_by":"auto","created_at":"2025-08-12 06:27:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105002,"visible":true,"origin":"","legend":"\u003cp\u003eThe Criteria to Determine Compositional and Idiomatic Particles in PV Construction\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7222728/v1/94293d46752454664baedd4c.png"},{"id":88855408,"identity":"0ff48ae5-b98a-4f8e-8707-67f7afcb667b","added_by":"auto","created_at":"2025-08-12 06:27:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":112701,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eRandom sample of 10 concordance lines taken from Sketch Engine for the particle “out”\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7222728/v1/2ca1cd36dddf6ac523c84ae0.png"},{"id":88855578,"identity":"a2b9758b-2531-436e-b26a-395daa1dd95a","added_by":"auto","created_at":"2025-08-12 06:35:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":253382,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eA random sample of concordance lines from the Sketch Engine\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7222728/v1/1fb280c0a20b9e79e6923738.png"},{"id":88855411,"identity":"d3a91b12-8711-4d1c-9d5c-2f64cfabb141","added_by":"auto","created_at":"2025-08-12 06:27:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":43588,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePedagogical preferences suggested by Johnson (1987)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7222728/v1/f0a5c5614bad67f2bde7aef1.png"},{"id":88855414,"identity":"1979ba77-f052-40c4-8e25-47bf3ad10bb6","added_by":"auto","created_at":"2025-08-12 06:27:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":31334,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePhraseological Spectrum Model\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7222728/v1/9f2459b5cb64ee5e6c0d7633.png"},{"id":89125440,"identity":"37ff7ea4-5082-41a6-97f8-d5e6ccc74058","added_by":"auto","created_at":"2025-08-15 03:46:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1519023,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7222728/v1/18df7da7-00d8-426f-b8ac-96b3b33c4b41.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Dual Nature of Directional Particles in Academic Phrasal Verbs: A Constructionist Corpus Analysis of 'Out', 'Up', and 'Down' in the BAWE Corpus","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAlthough phrasal verbs are regarded as complete and meaningful constructions in themselves, they possess a dynamic nature in composition, and this dynamism plays a significant semantic role. It has also been frequently observed that the constituents of phrasal verbs, specifically adverbial particles, are often overlooked in studies of phrasal verbs, even though they play a crucial role in forming multiword expressions centered around verbs and contribute to their meanings. The dual nature of the particles encompasses both a compositional aspect, where they play a crucial role in the meaning-making of the verb, and a frozen aspect, where the meanings are essentially idiomatic; individual words do not contribute significantly to the overall meaning.\u003c/p\u003e\u003cp\u003eAs a small functional unit, an adverbial particle, whether a preposition or an adverb, is considered to modify the meanings of verbs within phrasal verb constructions. Thornbury\u0026rsquo;s (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) classification of phrasal verbs into four categories, namely, intransitive, transitive separable, transitive inseparable, and three-part, remains a syntactic classification. Semantically, Celce-Murcia and Larsen-Freeman (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) have classified phrasal verbs into three types: literal, where the composition helps identify meanings; aspectual, in which meanings remain opaque or partially transparent; and thoroughly idiomatic, where meanings do not depend on any of the constituent parts (Zamin et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This study is based on two main categories: compositional and frozen particles. The compositional adverbial particles contribute to the overall meaning of the construction, as demonstrated by the phrase \u0026ldquo;take out.\u0026rdquo; For example, in the construction \"take me out of this room,\u0026rdquo; it is classified as compositional because \"take\" retains its meaning while \"out\" indicates an outward direction. Conversely, frozen particles are involved in the formation of idiomatic expressions, where the meanings of the core constituents are significantly altered, making it impossible to deduce the overall meanings from the individual verb or particle. For example, \u0026ldquo;break down\u0026rdquo; is a phrasal verb whose meanings may not be dependent on the verb \u0026ldquo;break\u0026rdquo; and the particle \u0026ldquo;down,\u0026rdquo; suggesting a downward direction.\u003c/p\u003e\u003cp\u003eNevertheless, there are phrasal verbs, such as \u0026ldquo;go up\u0026rdquo; and \u0026ldquo;take down,\u0026rdquo; that exhibit both compositional and frozen characteristics, which present a challenge for second language learners. They find it difficult to determine when the same particle acts as a fixed element versus a compositional component. This issue has been a central concern of this study, which focuses on second language acquisition and pedagogy.\u003c/p\u003e\u003cp\u003eInitial studies such as Biber et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) speculate that for Second Language (L2) learners, compositional phrasal verbs are more accessible to acquire due to their prior knowledge of the meanings of the constituents within the construction. The phrasal verb \u0026ldquo;go up,\u0026rdquo; as exemplified in \u0026ldquo;prices go up,\u0026rdquo; is more readily comprehensible as both \"go\" and \"up\" imply increase and rise, while \u0026ldquo;up\u0026rdquo; distinctly signifies upward movement in conjunction with the verb \"go.\" They contend that compositional structures enhance language acquisition and should be introduced as an initial step in teaching phrasal verbs.\u003c/p\u003e\u003cp\u003eHowever, the challenging aspect arises when particles alter their meanings or become fixed in the contribution of meanings. The dependence of meanings on how they are utilized poses a significant challenge for second language learners. For instance, the phrasal verb \u0026ldquo;run out\u0026rdquo; in the context of cricket and \u0026ldquo;run out of stock\u0026rdquo; in corporate affairs are entirely context-dependent.\u003c/p\u003e\u003cp\u003eSchmitt (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) has also noted that second language learners frequently struggle to distinguish between fixed and semi-fixed multiword expressions, particularly within a specific context. For these learners, grasping the fixed nature of particles is more challenging because, in fixed expressions such as idiomatic phrases, the constituent parts do not retain their core meanings. This poses problems for L2 learners when an entirely different and unfamiliar use in a particular context suggests different implications altogether. This implies that frozen expressions pose a significant challenge for L2 learners because of their fixed meanings. Without compositionality, L2 learners must rely on their native language and infer meanings through context and translation, which raises questions about the usefulness and accuracy of these methods (Cornell, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Sinclair \u0026amp; Renouf, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Sinclair, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). For fixed expressions, translation is not effective and may result in various unintended meanings in the target language. Subsequently, L2 learners fail to comprehend verbal expressions employing phrasal verbs without knowing what they refer to.\u003c/p\u003e\u003cp\u003eWe contend that the integration of frozen expressions into educational curricula is imperative. This methodology is crucial for contextualized learning and offers a viable pathway for second language learners to acquire typical fixed expressions without requiring an in-depth understanding of specific terminology. Nonetheless, this endeavor presents considerable challenges. Such a perspective is corroborated by Tono (2012), who asserts that L2 learners encounter substantial difficulties in understanding these fixed expressions. Biber et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) identify it as a key reason why phrasal verbs are not included in initial teaching materials, which creates extra challenges for intermediate and advanced learners when they encounter these constructions for the first time at their respective proficiency levels. This may explain why individuals rarely use phrasal verbs in their daily interactions, ultimately limiting the proficiency of second language learners. As previous research (Lightbown \u0026amp; Spada, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Spada, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) shows, second language learners tend to focus more on form and grammar. Simultaneously, phrasal verbs frequently evade this form-meaning conceptualization, thereby rendering them more challenging to acquire. For instance, the verb \"bring\" is straightforward and is typically understood by intermediate learners; however, when it is employed as \u0026ldquo;bring up,\" \u0026ldquo;bring in,\" and \u0026ldquo;bring about,\" the meanings of \"bring\" are no longer consistent.\u003c/p\u003e\u003cp\u003eIn light of this, Schmitt (2018) suggests the contextual use of phrasal verbs, which can help learners understand them more effectively, particularly through the use of multimedia and interactive exercises. He believes that corpus analysis, particularly in terms of frequency and concordances, significantly aids learners in using phrasal verbs correctly. The duality exhibited by particles in Phrasal Verb constructions serves either as a directional indicator or as an idiomatic element (Biber et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). During the process of grammaticalization, as Hopper and Traugott (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) suggest, their original meanings are either completely replaced or partially changed with idiomatic or more abstract senses. For similar reasons, Darwin and Gray (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) regard PVs, once lexicalized, as a challenging task for second language learners. Gardner and Davies (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) further confirm that second language learners avoid PVs due to this duality, resulting in either unpredictability or idiomatic opacity.\u003c/p\u003e\u003cp\u003eTo sum up, Phrasal verbs (PVs) are complex for second language learners due to their idiomatic and syntactic features, often leading learners to avoid them. Despite extensive research on their structure (Biber et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Celce-Murcia \u0026amp; Larsen-Freeman, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Gardener \u0026amp; Davies, 2007; Liu, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Schmitt, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Mahpeykar \u0026amp; Tyler, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), the functions of particles, especially directional adverbials like \u0026ldquo;out,\u0026rdquo; \u0026ldquo;up,\u0026rdquo; and \u0026ldquo;down\u0026rdquo;, remain underexplored in academic writing. This study aims to address this gap by utilizing BAWE preloaded in Sketch Engine (Kilgarriff et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), with a focus on directional particles across different genres. Mastery challenges include semantic opacity, varying frequency, fixedness, register sensitivity, and genre-specific use, such as in methodology sections versus essays. The study responds to key research questions:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHow do adverbial particles \u0026ldquo;out,\u0026rdquo; \u0026ldquo;up,\u0026rdquo; and \u0026ldquo;down\u0026rdquo; operate in academic phrasal verb constructions, either through their composition or idiomatic meanings?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat are the frequency and distribution patterns of these PVs across genres in the BAWE corpus?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat pedagogical and linguistic implications do these patterns have for second language learners?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"LITERATURE REVIEW","content":"\u003cp\u003eAs established in the preceding section, Phrasal Verbs (PVs) continue to present considerable challenges for second language (L2) learners due to their ambiguous meanings, flexible syntactic structures, and context-dependent idiomatic usage (Gardner and Davies, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Schmitt, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Alangari et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Unlike single-word verbs, PVs comprise a verb combined with one or more particles, forming multiword expressions that can range from entirely literal to highly idiomatic meanings. This variation complicates the learning process, particularly when their meanings cannot be inferred from individual components. These characteristics not only create lexical difficulties but also pose pragmatic and functional challenges, especially within academic writing.\u003c/p\u003e\u003cp\u003eA key linguistic challenge in learning phrasal verbs (PVs) is their varying degree of idiomaticity. Researchers such as Celce-Murcia and Larsen-Freeman (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) and Liu (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) describe PVs as existing on a continuum, ranging from transparent phrases like \"go down the stairs\" to fixed idiomatic expressions like \"point out flaws,\" which often defy literal interpretation. Learners rely heavily on memorization and context, unlike more compositional PVs, which can be understood by analyzing their meanings. Zamin et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) classify particles as either compositional, adding spatial sense, or frozen, part of fixed idioms. Hybrid forms, such as \"go up\" and \"take off,\" blur these categories.\u003c/p\u003e\u003cp\u003eL2 learners often avoid phrasal verbs (PVs), replacing them with more formal Latinate verbs (Thornbury, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e and \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Liao \u0026amp; Fukuya, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Schmitt, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Haugh \u0026amp; Takeuchi, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For example, 'conduct an experiment' is frequently used instead of 'carry out an experiment,' even though the latter sounds more natural in academic contexts. Such substitutions may reflect caution but reduce expressive variety and limit the use of common academic English expressions (Schmitt \u0026amp; Schmitt, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Learners' avoidance is also influenced by their first language (L1). Speakers of languages with few particles (e.g., Chinese) tend to use PVs less often. In contrast, speakers of particle-rich languages (e.g., German) often overuse PV structures based on their native syntax (Kamarudin, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Wei (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) has meaningfully shown that learners with higher proficiency use significantly more PVs.\u003c/p\u003e\u003cp\u003eInitial research (Biber et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) studied how often phrasal verbs appear in different textual genres but offered limited understanding of how genre affects the semantic meaning of particles. Most studies mainly look at particle occurrence rates and often overlook how genre influences whether PVS are idiomatic or compositional. For example, \"set up\" in scientific texts usually works procedurally, while in philosophical essays, it often refers to a theoretical idea. This study aims to explore how directional particles (out, up, down) change their meanings and usage across various academic genres, focusing not just on frequency but also on how genre-specific patterns shape their interpretation.\u003c/p\u003e\u003cp\u003eDirectional particles have experienced diachronic delexicalization, whereby their original spatial meanings have become increasingly abstract over time (Hopper \u0026amp; Traugott, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). This process of grammaticalization is particularly observable in academic writing, where the behavior of particles varies according to genre. In scientific disciplines, particles such as \"down\" generally maintain literal, procedural meanings, exemplified by their use in breaking down compounds, which corresponds with the demand for precision in language (Biber et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Darwin \u0026amp; Gray, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Baldwin \u0026amp; Villavicencio, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Baldwin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Conversely, texts within the humanities frequently adopt particles as rhetorical idioms, exemplified by phrases such as \"sum up arguments\" or \"point out flaws,\" utilized for evaluative purposes (Gardner \u0026amp; Davies, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Biber \u0026amp; Jones, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Paquot, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Additionally, the particle \"up\" functions as a semantic pivot, oscillating between literal uses (e.g., \"build up pressure\") and figurative uses (e.g., \"build up a theory\"), with these functions being influenced by genre and context (Lindner, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1981\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis variation reveals a more profound theoretical divide: cognitive models, such as those proposed by Lindner (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), concentrate on image schemas to elucidate the spatial and metaphorical meanings of particles, whereas corpus methodologies (e.g., Gardner and Davies, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) analyze distributional data. This research integrates these perspectives by employing Goldberg's (2006) Construction Grammar, which interprets PVs as genre-specific constructions influenced by disciplinary standards and communication objectives, thereby providing an explanation for grammaticalization and idiomaticity within genres. Prior studies have predominantly neglected the significance of directional particles in academic language, instead concentrating on aspectual particles such as \u0026lsquo;off\u0026rsquo; and \u0026lsquo;through\u0026rsquo;, without developing comprehensive models for directional particles across various genres (Liu, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Siyanova-Chanturia \u0026amp; Martinez, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Despite their increasing prominence, constructionist grammar and phraseology theories remain underutilized in genre-specific corpus analysis. This study addresses this gap by examining 'out', 'up', and 'down' within academic genres in the BAWE corpus, offering valuable insights and pedagogical recommendations.\u003c/p\u003e\u003cp\u003eThe tools of corpus linguistics are vital for the analysis of PVs, notwithstanding certain limitations. Researchers frequently reference various frequency thresholds, ranging from 5 to 40 hits per million. In this investigation, we employ five hits to identify pertinent and occasionally infrequent academic PVs. Due to the variability in idiomaticity coding, our methodology encompasses semantic, syntactic, and contextual analyses to ensure accuracy. Extensive corpora, such as the BNC and COCA, afford a comprehensive overview of language utilization but may obscure register boundaries. Conversely, BAWE provides distinct disciplinary categories, thereby facilitating genre classification.\u003c/p\u003e\u003cp\u003eResearch has indicated particular challenges in language teaching methodologies. Many conventional resources depend on isolated PV lists (Cornell, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1985\u003c/span\u003e), predominantly emphasizing compositional meanings, despite the fact that academic language is abundant in idioms (Schmitt, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Strategies involving L1 transfer are infrequently employed, potentially diminishing their effectiveness (Jiang, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Although approaches such as corpus-based examples (Gardner \u0026amp; Davies, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), multimedia contextualization (Schmitt \u0026amp; Schmitt, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and formulaic instruction (Wray, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) are available, they have not been systematically organized according to grammatical complexity. This study proposes a novel model that advances from basic (compositional) to hybrid, and ultimately to idiomatic, in accordance with various genre functions.\u003c/p\u003e\u003cp\u003eThis study introduces a Genre-Construction Interface Model that combines corpus linguistics, Construction Grammar, and teaching strategies, drawing on Goldberg\u0026rsquo;s (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) form-meaning pairs and Hopper and Traugott\u0026rsquo;s (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) paths of grammaticalization. It positions directional particles along a spectrum of phraseological units to illustrate features like semantic bleaching and genre-specific variations. The research applies Construction Grammar to directional particles within academic discourse, addressing issues related to frequency, function, idiomaticity, and compositionality. It addresses four key gaps: providing quantitative data on genre-particle interactions, focusing on neglected directional particles, developing genre-aware teaching methods for L1 language types, and integrating cognitive and corpus-based approaches. It redefines directional particles as vital, genre-specific skills for enhancing academic literacy in English as a second or foreign language.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003eThis study used a mixed-methods corpus linguistic approach to examine the duality of adverbial particles (out, up, down) in academic phrasal verbs. It combined quantitative corpus analysis with qualitative contextual analysis, following established protocols (Gardner \u0026amp; Davies, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe BAWE corpus, representing authentic academic writing across disciplines and proficiency levels (Heuboeck et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hyland, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), contains 6.5069\u0026nbsp;million words and over 3000 texts across four proficiency levels and 34 disciplines in four major fields.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBAWE Categorization into Major Fields\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eField\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e% Corpus\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGenres Included\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArts and Humanities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEssays, critiques\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCase studies, proposals\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLife Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMethodology recounts\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExplanations, design specs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe data was extracted from the Sketch Engine (Kilgarriff et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) using Corpus Query Language (CQL) with the pattern: [word=\"out\" | word=\"up\" | word=\"down\" and tag=\"RP\"] [lemma=\".\"] [tag=\"VB.\"] {0,6} and [word=\"down\" and tag=\"RP\"] [!tag=\"BE\"]. The parameter captures 0\u0026ndash;6 tokens between a verb and a particle, limited to adverbial particles, excluding the be +\u0026thinsp;particle construction with !tag=\"be\". Further exclusion criteria are provided below.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExclusion criteria for directional particles\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncluded\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExcluded\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e% Excluded\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSyntactic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVerb\u0026thinsp;+\u0026thinsp;particle constructions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrepositional uses\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSemantic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDirectional particles\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAspectual particles (e.g.,\u0026nbsp;\u003cem\u003efinish up\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFunctional\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePVs with lexical verbs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCopular constructions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOur criteria are founded upon established best practices within the field of corpus linguistics. Research in this area exhibits variation in the thresholds set for lexical significance, which are contingent upon the specific type of corpus and overarching research objectives. Hunston (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) recommends a minimum of 40 hits per million words to ensure reliability. Bestgen (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) suggests a range of 10 to 40 hits, depending on contextual factors. O'Keeffe et al. (2007) advise a threshold of 4 hits per million, while also stipulating a minimum of 40 raw hits for validity. These criteria are adjusted to maintain an appropriate balance between accuracy and relevance. For the purposes of this study, five hits per million and 40 raw hits are employed for academic PVS.\u003c/p\u003e\u003cp\u003eTo define idiomaticity in phrasal verbs, a semantic classification was employed, evaluating compositionality, replaceability, object abstractness, and fixedness. This approach ensured a consistent classification of idiomatic versus literal usages.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe reliability metrics encompass Cohen's κ, which is .89, signifying near-perfect agreement. Discrepancies were resolved through consensus, and a 95% confidence interval for accuracy was established at \u0026plusmn;\u0026thinsp;2.1%.\u003c/p\u003e\u003cp\u003eFrequency profiling with normalized counts per million words. Genre distribution mapped using chi-squared tests and binomial logistic regression: logit (Idiomatic) = β₀ + β₁(Genre) + β₂(Discipline) + β₃(Particle).\u003c/p\u003e\u003cp\u003e\u003cb\u003eQualitative Analytical Procedure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe have analyzed concordance lines by academic purpose, including procedures, critiques, and essays, and subsequently validated the statistics. Fisher's Exact Test was employed for low-frequency PVs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), complemented by bootstrap resampling (1,000 iterations) to determine confidence intervals. The Sketch Engine enables the comparison of four academic genres for each particle and phrasal verb, encompassing frequency and density. These limitations were mitigated through rigorous statistical validation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eData Validation through Mitigation Strategies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLimitation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMitigation Strategy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eValidation Outcome\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLimited particle scope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExplicit focus on high-frequency directional particles\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFisher's test confirmed representativeness (p\u0026thinsp;=\u0026thinsp;.018)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBAWE excludes spoken data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCompared with the BASE corpus samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92% consistency in PV patterns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThreshold arbitrariness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFisher's Exact Test validation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAll thresholds are significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003cp\u003eThrough bootstrap resampling, we confirmed 95% confidence that our frequency thresholds captured\u0026thinsp;\u0026gt;\u0026thinsp;89% of pedagogically relevant PVs while maintaining statistical robustness (CI: 86.7\u0026ndash;91.3%).\"\u003c/p\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cp\u003eThis section presents a triangulated analysis addressing the study's three research questions through an integrated quantitative, qualitative, and statistical perspective. Building on Construction Grammar principles (Goldberg, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and frameworks of idiomaticity (Siyanova-Chanturia \u0026amp; Martinez, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), we demonstrate how academic genres influence particle semantics, with direct implications for L2 teaching.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOverall Distribution and Semantic Duality (RQ1)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 9,866 phrasal verb (PV) constructions with target particles were extracted from BAWE (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Importantly, 78.25% showed idiomatic meanings, supporting Schmitt and Schmitt's (2020) avoidance hypothesis.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticle Distribution in Academic PVs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParticle\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrozen %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCompositional %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2; (vs. BNC)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOut\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e98.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e892.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e328.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1226\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e63.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e167.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026gt;p\u0026thinsp;\u0026lt;\u0026thinsp;.001; BNC reference: Gardner and Davies (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe extreme χ\u0026sup2; values (e.g., χ\u0026sup2; = 892.4, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 for 'out'; Cramer\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.42) demonstrate that academic PVs occur 5.7 times more densely than in general English. Similarly, the influence of 'up' (χ\u0026sup2; = 328.7, p\u0026thinsp;\u0026lt;\u0026thinsp;.001; V\u0026thinsp;=\u0026thinsp;0.25) and 'down' (χ\u0026sup2; = 167.2, p\u0026thinsp;\u0026lt;\u0026thinsp;.001; V\u0026thinsp;=\u0026thinsp;0.18) exhibit strong effect sizes, emphasizing the significance of these associations. Cramer\u0026rsquo;s V was calculated as:\u003c/p\u003e\u003cp\u003eV\u0026thinsp;=\u0026thinsp;χ\u0026sup2;/n\u0026times;(k\u0026thinsp;\u0026minus;\u0026thinsp;1), where n\u0026thinsp;=\u0026thinsp;9,866 and k\u0026thinsp;=\u0026thinsp;2. Effect sizes are consistent with Cohen\u0026rsquo;s benchmarks (V\u0026thinsp;=\u0026thinsp;0.1: small; 0.3: medium; 0.5: large).\u003c/p\u003e\u003cp\u003eBinomial regression indicates that particle type predicts idiomaticity (β\u0026thinsp;=\u0026thinsp;2.17, SE\u0026thinsp;=\u0026thinsp;0.18, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), with \"out\" being 84.7 times more likely than \"down\" to be idiomatic (OR\u0026thinsp;=\u0026thinsp;84.7, CI: 76.2\u0026ndash;94.1). This supports grammaticalization pathways (Hopper and Traugott, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), suggesting near-complete semantic bleaching of \u0026ldquo;out\u0026rdquo; in \u0026ldquo;carry out,\u0026rdquo; whereas \u0026ldquo;down\u0026rdquo; remains associated in \u0026ldquo;break down,\u0026rdquo; and \u0026ldquo;up\" holds an intermediate position.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunctional Distribution of \"Out\" PVs\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGiven that the study focuses on the compositional and frozen characteristics, phrasal verbs are evaluated based on their frequency, structure, and semantic features. Analyzing all phrasal verbs within a single article proves challenging; therefore, only the top ten are discussed comprehensively, followed by an examination of the duality of adverbial particles. Utilizing the preloaded BAWE corpus in Sketch Engine and Corpus Query Language, we identified a total of 8,239 phrasal verbs. The data indicates that \u0026ldquo;carry out\" is the most prevalent in the BAWE corpus, constituting 29.50% of phrasal verb usage, with 6,469 occurrences and 4,836 instances with verbs. Excluding \u0026ldquo;be\u0026rdquo; forms and low-frequency collocations, \"out\" emerges as the most common adverbial particle at 57%, frequently paired with verbs. Those with over 40 occurrences and five relative hits are listed below.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequencies and percentages of phrasal verbs with particle \u0026ldquo;out\u0026rdquo;\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReltv. Freq.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e% from of PVs\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecarry out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e186.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epoint out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e95.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efind out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eset out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ework out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eturn out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003erule out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elay out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003estand out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ego out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecome out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e3430\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e411.45\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e65.12\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe phrasal verb \"carry out\u0026rdquo; constitutes over 30% of instances involving particles with lexical verbs, amounting to 1,554 occurrences. It is predominantly found in essays (191), critiques (171), and design specifications (57), underscoring its significance in formal contexts. All occurrences are established fixed expressions devoid of compositional meaning. While idiomatic usages are prevalent, their interpretations are neither transparent nor adaptable. The object types tend to be abstract, and substituting words with synonyms does not necessarily retain the original meaning, thereby highlighting the critical role of context for precise comprehension. The phrasal verb \"point out\" accounts for 15% of usage, totaling 795 instances. Contextual analysis reveals its primary appearance in non-literal contexts, with subsequent frequent usage in that-clauses (411), constructions involving \"the\u0026rdquo; and abstract nouns (288), or abstract nouns alone. This supports the observation of its fixed usage within the BAWE corpus. A comparable analysis of \u0026ldquo;find out\u0026rdquo; indicates its greater prevalence in essays (31), methodology recounts (24), critiques (19), and problem questions (19). Collectively, \"carry out,\" \"point out,\" and \"find out\" represent over fifty percent of related phrasal verbs, which are predominantly employed in analytical, critical, investigative, and argumentative academic writing.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese idiomatic phrasal verbs with \u0026ldquo;out\" generally do not significantly alter their fundamental meanings in academic writing. For instance, \u0026ldquo;go out\u0026rdquo; and \u0026ldquo;work out\" demonstrate that \"out\u0026rdquo; sometimes contributes to the meaning while other times functions idiomatically. \u0026ldquo;Go out\u0026rdquo; predominantly employs \"out\" as a particle, analogous to 'going out to work.' It is often followed by words such as \"to,\u0026rdquo; \u0026ldquo;with,\u0026rdquo; \u0026ldquo;and,\u0026rdquo; or \u0026ldquo;on,\u0026rdquo; with only nine out of forty-eight occurrences being idiomatic. Conversely, \u0026ldquo;come out\u0026rdquo; is primarily idiomatic, manifesting 29 times out of 45. \u0026ldquo;Set out\u0026rdquo; is chiefly idiomatic in scholarly essays to denote aiming to achieve, used 67 times, frequently with phrases like \u0026ldquo;set out to accomplish,\u0026rdquo; or following \u0026ldquo;the\u0026rdquo; and \u0026ldquo;in\u0026rdquo; with abstract nouns. These patterns indicate that these phrases are predominantly non-literal and can often be employed unchanged. Similar patterns are observed with \u0026ldquo;turn out,\u0026rdquo; \u0026ldquo;stand out,\u0026rdquo; and \u0026ldquo;rule out,\u0026rdquo; which are also frequently idiomatic.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop PVs with Particle \u0026ldquo;Out\u0026rdquo; with their academic functions and Genre Ratio\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIdiomatic %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAcademic Function\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGenre Ratio\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarry Out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResearch Processes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMethodology: 8.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoint out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIdentifying limitations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCritique: 12.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFind out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReporting discoveries\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEssay: 6.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSet Out\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStating Objects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProposal: 9.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe findings may help L2 learners utilize phrasal verbs effectively in academic domains.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunctional Distribution of \u0026ldquo;up\u0026rdquo; in the BAWE Corpus\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe BAWE corpus documents 12,528 instances of the word \"up,\" with 4,216 instances functioning as particles within phrasal verbs, at a frequency of 505 per million (0.051%). \"Up\" ranks as the second most frequent particle associated with lexical verbs in English academic writing. The subsequent phrasal verbs satisfy the criteria established for this study.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhrasal Verbs with Particle \u0026ldquo;up\u0026rdquo; in the BAWE Corpus\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLemma\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRltv. Freq.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e% of PVs\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eset up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e561\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emake up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e404\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebuild up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epick up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003etake up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecome up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eend up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esum up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eopen up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003egive up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eback up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebring up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecatch up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003egrow up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003espeed up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ego up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efollow up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebreak up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003edraw up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003estand up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ekeep up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e2820\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e338.28\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e22.41\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe table indicates that \u0026ldquo;set up\u0026rdquo; is the most prevalent phrasal verb (PV) with the particle \u0026ldquo;up\u0026rdquo; in this list, followed by \u0026ldquo;make up\u0026rdquo; and \u0026ldquo;build up,\u0026rdquo; which collectively account for over 10% of all instances of \u0026ldquo;up\u0026rdquo; in the concordance. Most occurrences demonstrate their idiomatic and constructive uses. They typically refer to processes such as establishing experiments, actions like installing instruments, and adjustments such as arranging a camera, among others. Below are the concordance lines selected at random for \u0026ldquo;up.\u0026rdquo;\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe two most prevalent phrasal verbs associated with construction are 'set up' and 'make up.' 'Set up' appears 561 times across the corpus, predominantly within essays, case studies, critiques, and methodology sections, thereby signifying its prominence within the scientific domain. It is employed to describe experiments, research designs, and practical applications, with 46 of the 111 occurrences involving 'up' as an inseparable particle, frequently pertaining to plans or equipment. Approximately 41% of these instances are idiomatic, while 59% are literal, underscoring its relevance to academic and process-oriented writing rather than the humanities or social sciences. Conversely, 'make up' is encountered 404 times in diverse contexts, notably in essays (188 occurrences), often within argumentative, analytical, or descriptive compositions. Its moderate utilization in methodology (63 instances) and explanatory sections (57 instances) indicates their role in facilitating clarity and structural coherence.\u003c/p\u003e\u003cp\u003eThe phrasal verb \"make up\" is seldom employed in formal writing, such as design specifications, proposals, and research reports, primarily for descriptive purposes within the soft sciences. Conversely, the phrasal verb \"Build up\" is prevalent, with over 30 occurrences per million tokens, particularly in essays (89 instances), critiques (29), case studies (29), and other texts. \"Pick up\" appears 174 times, chiefly in essays (63), design specifications (22), and critiques (21). \"Take up\u0026rdquo; occurs 151 times, predominantly in essays (72), as well as in explanatory texts and case studies. \"Come up\" is found 151 times, mainly in essays (51), and also in narratives and critiques. \"End up\" appears 141 times, primarily in essays (93), followed by critiques. \"Sum up\u0026rdquo; occurs 139 times, mainly in essays (90), with some instances in critiques and explanatory texts. Most \"up\"-phrasal verbs are common in essays, especially those of argumentative and analytical nature, demonstrating discursive use, tone, and roles; they are more prevalent in the humanities than in the sciences. Further research is required to distinguish between formal and informal usages. The functions of these phrasal verbs include \"sum up\u0026rdquo; in conclusions, \u0026ldquo;end up\u0026rdquo; for unintended consequences, and \u0026ldquo;take up\" at the beginning of discussions. Even less frequent verbs such as \"give up\" and \u0026ldquo;back up\" serve important broader functions. In academic writing, \"up\" often marks procedures, descriptions, and processes, with meanings that are both variable and fixed. For example, \"end up\" frequently indicates outcomes with a negative connotation, \"give up\u0026rdquo; signifies abandonment, and \"break up\u0026rdquo; is used to describe political divisions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe PVs with \u0026ldquo;Up\u0026rdquo; across Genre\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIdiomatic %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% in sciences\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e% in Humanistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eΔGenre (p)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSet up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMake up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBuild up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnd up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe Hybrid Semantics of \"Up' demonstrates a balanced duality in genre determination. Literal patterns encompass methodological dominance within the field of physics and idiomatic preferences prevalent in the humanities. Aspectual phrasal verbs (e.g., \"end up,\" \"sum up\") are consistently fixed, corroborating the aspectual category proposed by Celce-Murcia and Larsen-Freeman (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The BAWE corpus contains numerous compositional phrasal verbs, linking 'up' to meanings such as direction; for example, 'build up' can be partly compositional ('built up from basic principles') or metaphorical ('build up tensions'). 'Go up' is employed both literally and metaphorically ('prices went up'). 'Speed up' and 'stand up' are fully compositional. Some flexible phrasal verbs, such as 'set up,' 'take up,' and 'make up,\" are frequently used in both literal and idiomatic contexts. Methodological approaches and case studies often utilize compositional phrasal verbs, e.g., 'setting up the apparatus,' whereas academic essays tend to favor idiomatic expressions like 'summing up the argument.' Critiques and proposals exhibit mixed usage, e.g., 'taking up a position' and 'building up evidence.' In scientific discourse, compositional phrasal verbs are predominantly employed in introductions and methods sections, whereas idiomatic phrasal verbs predominate in discussions and conclusions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunctional Distribution of \u0026lsquo;down\u0026rdquo; in the BAWE Corpus\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe particle \u0026ldquo;Down\u0026rdquo; is documented 1799 instances within the BAWE corpus, corresponding to a relative frequency of 255. Within phrasal verbs, it occurs 1307 times, serving as a conventional adverbial particle with multiple functions. It is incorporated into 146 phrasal verbs, with an average incidence of 155 instances per million, although only six surpass the threshold of 40 occurrences and 5 per million.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhrasal Verbs with Particle \u0026ldquo;down\u0026rdquo; in the BAWE Corpus\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRltv. Freq.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e% of PVs\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebreak down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.62959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.03568\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eslow down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.39599\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.9368\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elay down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.31637\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.75331\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ego down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.63802\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.95821\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecut down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.03823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.85627\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e519\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e62.0182\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e10.54027\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe phrasal verb \u0026ldquo;break down\u0026rdquo; is employed 247 times, corresponding to a frequency of 29.62 per million. Although it is less prevalent than \u0026ldquo;carry out\u0026rdquo; or \u0026ldquo;set up,\u0026rdquo; it maintains significant importance. Its primary occurrence is within essays (90 instances), comprising 90% of its usage, which suggests it is less confined to specific genres. Additionally, it appears in the methodology section (40), critique (29), explanation (24), and case studies (14), predominantly as a frozen particle with verbs. Its density is comparatively higher in other genres than in essays, and it sometimes combines with verbs to preserve meaning. Although this phrasal verb frequently appears in academic writing alongside a compositional partner, it is also widely utilized within the soft sciences and humanities, often with a frozen particle as in \u0026ldquo;breaking down the entire framework of society.\u0026rdquo;\u003c/p\u003e\u003cp\u003eThis phrasal verb pertains to societal disintegration and emotional collapse, a term more frequently employed within abstract disciplines rather than scientific domains. It underscores the technical and metaphorical utilization of \u0026ldquo;break down\u0026rdquo; in scholarly discussions, serving functions in explanations, evaluations, deconstruction, and argumentation based on particle application. The phrasal verb 'slow down' possesses literal meanings in everyday contexts and more nuanced interpretations when used as a fixed particle. With a total of 95 occurrences, it is most commonly found in methodology sections (28 instances), followed by essays (21 instances), and research reports (12 instances). Genres such as critiques, case studies, and explanations generally feature fewer than ten examples. An illustrative example from a methodology source demonstrates typical usage, such as \u0026ldquo;slowing down\u0026rdquo; the pace or processes.\u003c/p\u003e\u003cp\u003eHowever, at the same time, we have instances where it shows partial compositionality and leans more toward idiomatic use, such as \u0026ldquo;slowing down of the growth in the Retardation phase\u0026rdquo;.\u003c/p\u003e\u003cp\u003eThe concordances demonstrate that the phrase \"slow down\u0026rdquo; primarily functions in descriptive contexts and causal analysis, particularly within the hard sciences. The phrasal verb \u0026ldquo;lay down\u0026rdquo; appears 86 times, predominantly in Essays (39 occurrences, with a density of 94.34%) and Critiques (15 occurrences), indicating its typical usage. The particle \u0026ldquo;down\u0026rdquo; infrequently serves a compositional purpose; for instance, in \"the dogs lay down\u0026rdquo; within Essays. Conversely, in critiques, the expression \u0026ldquo;laying down the criteria\u0026rdquo; generally possesses an idiomatic and conventional significance.\u003c/p\u003e\u003cp\u003eThis Phrasal Verb is predominantly observed within the disciplines of social sciences and humanities, fulfilling roles such as delineating theories and establishing legal frameworks. The final two instances, both containing the word \"down,\" are \u0026ldquo;go down\" (46 occurrences) and \u0026ldquo;cut down\" (42 occurrences). \"Go down\u0026rdquo; is seldom employed outside of idiomatic contexts in academic dialogue, with only 14 appearances in essays, predominantly accompanied by fewer than ten concordance lines. Its usage is more prevalent in methodological recapitulations, with an approximate increase of 225%, although it appears more frequently in essays, such as in expressions like \"economies going down.\" It is primarily utilized to analyze trends and changes over time. Similarly, \u0026ldquo;cut down\u0026rdquo; demonstrates moderate usage as a component of the particle and is frequently found in idiomatic contexts. It appears 14 times in essays and 12 times in case studies. The relative frequency in essays (69%) suggests it is not characteristic of this corpus type, whereas the density in case studies (366%) indicates that this PV is standard in such texts.\u003c/p\u003e\u003cp\u003eThis PV appears in policy suggestions, reduction, and environmental impacts, aligning more with hard sciences than the humanities. The concordance lines indicate that most instances are used metaphorically in an abstract sense to preserve figurative accuracy within academic contexts. They serve various academic functions, including explaining, trend analysis, evaluation, and making recommendations. Some genres also emphasize particular usages, such as idiomatic expressions in essays and explanatory functions in hard sciences. The compositional tendencies of this particle differ from others by maintaining stronger spatial semantics, as shown in the table.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSemantic Flexibility of \"Down\" PVs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCompositional Instances (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLiteral Meaning\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFigurative Extension\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreak down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMechanical failure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConceptual analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlow down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMechanical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEconomic decline\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGo down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReduced velocity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumerical reduction\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCut down\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e78.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePhysical reduction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResource conservation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRegression analysis has established that the Life Sciences exhibit 73.4% literal utilizations, in comparison to 62.2% idiomatic utilizations within the Social Sciences.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGenre-Driven Variation Patterns (RQ2)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGenre emerged as the most significant predictor of particle semantics (β\u0026thinsp;=\u0026thinsp;1.84, SE\u0026thinsp;=\u0026thinsp;.23, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), accounting for 38.7% of the variance in idiomaticity (R\u0026sup2;=.387). Humanities genres demonstrated an idiomatic density 2.3 times greater than that of the sciences.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenre-Mediated Particle Functions\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenre\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIdiomatic PVs (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequent Compositional PVs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrequent Idiomatic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDisciplinary Bias\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEssay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e84.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGo down (63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCarry Out (99.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHumanities: 5.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCritique\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e79.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSet up (41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePoint out (98.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSocial Sciences: 3.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethodology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBreak down (68%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRule out (96.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePhysical Sciences: Ref\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCase study\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSlow down (62%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFind Out (97.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLife Sciences:1.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026gt;p\u0026thinsp;\u0026lt;\u0026thinsp;.001, p\u0026thinsp;\u0026lt;\u0026thinsp;.01, p\u0026thinsp;\u0026lt;\u0026thinsp;.05; OR\u0026thinsp;=\u0026thinsp;Odds Ratio for idiomaticity vs. Physical Sciences\u003c/p\u003e\u003cp\u003eArgumentative PVs constitute 92.3% of idiomatic particle usage in essays within the humanities discipline. Abstract object constructions, such as \u0026ldquo;point out\u0026rdquo; flaws, exceed 99% (f\u0026thinsp;=\u0026thinsp;795), and \u0026ldquo;laid down\u0026rdquo; is entirely idiomatic (f\u0026thinsp;=\u0026thinsp;86). A notable binomial regression indicates variation in construction patterns involving verb\u0026thinsp;+\u0026thinsp;out +\u0026thinsp;abstract noun, with χ\u0026sup2; = 213.4, p\u0026thinsp;\u0026lt;\u0026thinsp;.001. The section on scientific methodology exhibits 68.5% of compositional particles accompanied by procedural PVs, including \u0026lsquo;set up apparatus\u0026rsquo; (59.1%) and \u0026lsquo;break down samples\u0026rsquo; (67.9%), observed as particle\u0026thinsp;+\u0026thinsp;concrete noun (φ\u0026thinsp;=\u0026thinsp;.73, p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003cp\u003eExamining the particle-specific semantic landscape, it can be asserted that with 98.4% idiomatic uses, \u0026ldquo;out\u0026rdquo; establishes its dominance in academic discourse, indicating complete semantic bleaching.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePedagogical Implications (RQ3)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur third research question on pedagogical implications outlines a way forward. The analysis yields three evidence-based pedagogical imperatives. First, PVs are genre sensitive and require targeted instruction. For example, methodology PVs like 'set up' are less common in critiques focusing on idiomatic expressions such as \u0026lsquo;point out' or 'sum up'. We also argue that genre-specific uses should be included in learning materials in contrastive contexts, like \u0026ldquo;set up the spectrometer\u0026rdquo; in Chemistry and \u0026ldquo;set up a theoretical framework\u0026rdquo; in Sociology. The third point emphasizes construction-based sequencing, where pedagogically, compositional prototypes are introduced first. Literal to figurative uses should be integrated into the material per Johnson\u0026rsquo;s (1987) classification.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 4: Pedagogical preferences suggested by Johnson (1987)\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSimilarly, second language instruction should incorporate idiomatic clusters. Phrasal Verbs (PVs) can be classified as analytical (e.g., point out, rule out) and procedural (e.g., set up, break down). Corpus analysis reveals patterns such as \u0026lsquo;conducting experiments\u0026rsquo; that offer alternatives, thereby supporting Schmit\u0026rsquo;s (2018) PV avoidance hypothesis; however, classroom validation remains necessary. Additionally, findings suggest enhancements to existing models. We propose a Phraseological Spectrum Model (PSM), founded on Sinclair\u0026rsquo;s (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) Idiom Principle, Howarth\u0026rsquo;s (1998) Spectrum, Wray\u0026rsquo;s (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) Formulaic Language Theory, and Granger and Paquot\u0026rsquo;s (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) Academic Phraseology Framework.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAcademic phrasal verbs also constitute genre-specific constructions, such as:\u003c/p\u003e\u003cp\u003eConstruction / Pattern: [Verb\u0026thinsp;+\u0026thinsp;Particle] GENRE\u0026thinsp;=\u0026thinsp;SEMANTIC_PROFILE\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eExample\u003c/strong\u003e\u003cp\u003e[SET\u0026thinsp;+\u0026thinsp;UP] Methodology\u0026thinsp;=\u0026thinsp;Procedural action\u003c/p\u003e\u003c/p\u003e\u003cp\u003eThese advances address the limitations in Gardner and Davies' (2007) frequency-based approach by integrating semantic and contextual aspects. The findings support the conclusion by showing how genre patterns from corpora can reshape phrasal verb teaching and enhance phraseological theory. The analysis connects Biber et al.'s (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) lexical framework with constructionist methods, providing a cohesive explanation of academic PV semantics.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study investigates the role of directional particles (out, up, and down) in academic phrasal verbs, providing three key insights with substantial implications. It demonstrates that 78.25% of their utilization is idiomatic, with \u0026lsquo;out\u0026rsquo; entirely idiomatic (98.4%), \u0026lsquo;up\u0026rsquo; partially idiomatic (64.3%), and \u0026lsquo;down\u0026rsquo; predominantly literal (63.2%). This gradient aligns with grammaticalization theory, wherein spatial meanings diminish to develop abstract, genre-specific functions.\u003c/p\u003e\u003cp\u003eGenre serves as the primary predictor of particle semantics, accounting for 38.7% of the variation in idiomatic usage (β\u0026thinsp;=\u0026thinsp;1.84, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Humanities genres exhibit more than double the idiomatic density of scientific genres, with essays at 84.2% compared to 52.3% in methodological sections. Construction patterns vary: humanities tend to favor verb\u0026thinsp;+\u0026thinsp;particle\u0026thinsp;+\u0026thinsp;abstract noun (e.g., point out limitations), whereas scientific writing prefers particle\u0026thinsp;+\u0026thinsp;concrete noun (e.g., break down samples). These findings illustrate that academic genres significantly influence rhetorical objectives and the employment of particles within phrasal verbs.\u003c/p\u003e\u003cp\u003eThe research has demonstrated that directional particles within academic discourse are genre-specific constructions rather than merely freely combinable words. This observation necessitates a reevaluation of phrasal verbs within the framework of Construction Grammar (Goldberg, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), where form-meaning pairings exhibit variation across different genres. For instance, \u0026ldquo;SET UP\u0026rdquo; in methodological contexts signifies procedure, whereas in the humanities, it denotes abstract frameworks. This insight clarifies the ongoing debate concerning idiom compositionality and highlights the significance of recurring particle patterns in scholarly language.\u003c/p\u003e\u003cp\u003ePedagogically, the findings suggest three priorities. First, instruction should focus on genre-specific sequencing: learners need to learn compositional PVs common in scientific language (like \"set up\" or \"break down\") before idiomatic clusters in the humanities (such as \"point out\" or \"lay down\"). Second, teachers should use construction-based scaffolding, such as visual aids like image schemas (Johnson, 1987), to help students grasp literal-figurative shifts (e.g., from \"go down stairs\" to \"prices go down\"). Third, the research recommends L1-sensitive strategies, including creating contrastive exercises for speakers of particle-rich languages and activities to reduce avoidance in particle-poor languages.\u003c/p\u003e\u003cp\u003eThis research provides both theoretical and pedagogical contributions; however, it also exhibits certain limitations. It depends on the BAWE corpus, focusing solely on written academic English, thereby excluding spoken registers. Future research should incorporate the BASE corpus for comparative analysis and investigate less frequent aspectual particles, such as 'off' or 'through', across various disciplines to attain a more comprehensive understanding of phrasal verb usage. Furthermore, subsequent studies might explore how learners internalize genre-particle constraints over time, employ computational models for genre-aware phrasal verb recommendations, and compare grammaticalization pathways among English learners from different L1 backgrounds to evaluate the influence of L1 on PV acquisition. Overall, this study demonstrates that adverbial particles in academic writing constitute a genre-mediated spectrum shaped by discipline-specific conventions. By employing corpus-based, genre-sensitive methodologies, educators can redefine phrasal verbs from potential obstacles into rhetorical instruments that enhance scholarly and disciplinary fluency.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics and Consent to Publish declarations\u003c/h2\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e1. T. Q. Conceptualized, wrote the main manuscript, and curated data.2. A. T. formatted the manuscript and researched previous studies.3. S.K. provided overall supervision and helped with the technicalities. 4. N.H. reviewed the manuscript and suggested the changes.5. S. A. A. G. assisted in data collection for the paper.6. I.A.S. proofread and provided feedback.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe have used Grammarly, a software designed to enhance language clarity and precision. However, it has been carefully reviewed to ensure that the core idea remains unchanged.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eWe have utilized the British Academic Written English (BAWE) corpus, preloaded in the Sketch Engine (Kilgarriff et al., 2014), and it is accessible through the built-in interface of the Sketch Engine. It is freely available for subscribers at: https://app.sketchengine.eu/#dashboard?corpname=preloaded%2Fbawe2\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlangari, M., Jaworska, S., \u0026amp; Laws, J. (2020). Who\u0026rsquo;s afraid of phrasal verbs? The use of phrasal verbs in expert academic writing in the discipline of linguistics. \u003cem\u003eJournal of English for Academic Purposes, 43\u003c/em\u003e, 100814. https://doi.org/10.1016/j.jeap.2019.100814\u003c/li\u003e\n\u003cli\u003eBaldwin, T., Bannard, C., Tanaka, T., \u0026amp; Widdows, D. (2003). An empirical model of multiword expression decomposability. In \u003cem\u003eProceedings of the ACL 2003 Workshop on Multiword Expressions: Analysis, Acquisition and Treatment\u003c/em\u003e (pp. 89\u0026ndash;96). Association for Computational Linguistics. https://doi.org/10.3115/1119282.1119294\u003c/li\u003e\n\u003cli\u003eBaldwin, T., \u0026amp; Villavicencio, A. (2002). Extracting the unextractable: A case study on verb-particles. In D. Roth \u0026amp; A. van den Bosch (Eds.), \u003cem\u003eProceedings of the 6th Conference on Natural Language Learning (CoNLL-2002) \u0026ndash; Volume 20\u003c/em\u003e (pp. 1\u0026ndash;7). Association for Computational Linguistics. https://doi.org/10.3115/1118853.1118854\u003c/li\u003e\n\u003cli\u003eBestgen, Y. (2018). Evaluating the frequency threshold for selecting lexical bundles by means of an extension of the Fisher\u0026rsquo;s exact test. \u003cem\u003eCorpora, 13\u003c/em\u003e(2), 205\u0026ndash;228. https://doi.org/10.3366/cor.2018.0144\u003c/li\u003e\n\u003cli\u003eBiber, D., \u0026amp; Jones, J. K. (2009). Quantitative methods in corpus linguistics. In A. L\u0026uuml;deling \u0026amp; M. Kyt\u0026ouml; (Eds.), \u003cem\u003eCorpus linguistics: An international handbook\u003c/em\u003e (pp. 1286\u0026ndash;1304). Mouton de Gruyter. https://doi.org/10.1515/9783110213881.2.1286\u003c/li\u003e\n\u003cli\u003eBiber, D., Conrad, S., \u0026amp; Reppen, R. (1999). \u003cem\u003eLongman grammar of spoken and written English\u003c/em\u003e. Pearson Education.\u003c/li\u003e\n\u003cli\u003eCelce-Murcia, M., \u0026amp; Larsen-Freeman, D. (1999). \u003cem\u003eThe grammar book: An ESL/EFL teacher\u0026rsquo;s course\u003c/em\u003e. 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A corpus-based study on the use of phrasal verbs in Malaysian secondary school textbooks. \u003cem\u003eInternational Journal of Applied Linguistics and English Literature, 8\u003c/em\u003e(6), 76\u0026ndash;84. https://doi.org/10.7575/aiac.ijalel.v.8n.6p.76\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Phrasal Verbs, Adverbial Particles, Corpus Linguistics, L2 Acquisition, Idiomatic and Compositional Particles, Academic Writing, Construction Grammar, EAP Pedagogy","lastPublishedDoi":"10.21203/rs.3.rs-7222728/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7222728/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study employs Construction Grammar and cognitive linguistic frameworks to investigate the dual semantic functions of directional adverbial particles ('out', 'up', 'down') within phrasal verbs in the context of English academic writing. Utilizing Corpus Query Language (CQL) within Sketch Engine, a total of 9,866 instances of phrasal verbs from the British Academic Written English (BAWE) corpus were analyzed. The results demonstrate that 78.25% of these usages are idiomatic, with significant variation observed across different genres (χ\u0026sup2; = 892.4, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Notably, 'out' exhibits an idiomatic usage rate of 98.4%, whereas \"down' remains predominantly compositional at 63.2%. It is recommended that corpus-based examples, contextual learning, and genre-specific instruction be utilized to facilitate the acquisition of phrasal verbs. The findings substantiate the notion that targeted instruction of phrasal verbs can enhance the academic writing skills of learners of English as a second language. This research integrates corpus linguistics with Construction Grammar (Goldberg, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and cognitive semantics (Lakoff, 1987) to explore directional particles as schematic constructions. Within this framework, literal usages preserve their spatial semantics, whereas idiomatic extensions exemplify metaphorical mappings.\u003c/p\u003e","manuscriptTitle":"The Dual Nature of Directional Particles in Academic Phrasal Verbs: A Constructionist Corpus Analysis of 'Out', 'Up', and 'Down' in the BAWE Corpus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-12 06:27:20","doi":"10.21203/rs.3.rs-7222728/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ac01be33-485d-4bb5-8a11-b25c99b8dc9e","owner":[],"postedDate":"August 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-15T03:38:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-12 06:27:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7222728","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7222728","identity":"rs-7222728","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}