Beyond Winners and Losers: Collective Mental Time Travel Pathways Buffer Future Agency after Elections

Beyond Winners and Losers: Collective Mental Time Travel Pathways Buffer Future Agency after Elections | 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 Beyond Winners and Losers: Collective Mental Time Travel Pathways Buffer Future Agency after Elections Elif Sozer, Meymune Topcu, Aysecan Boduroglu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6789456/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 Research on collective mental time travel has shown thematic links between past and future events, but how specific events cue past and future events in relation to sociopolitical identity remains underexplored. Connecting the collective past to the future, we primarily focused on event characteristics to identify collective mental pathways using a data-driven, bottom-up approach. We focused on the 2023 Turkish Presidential Election as a pivotal event anchoring collective memories and related future projections. Using representative in-person interviews, we asked participants to evaluate the election, recall related past and future collective events, and rate each event’s characteristics (e.g. Valence, Vividness, Agency, Importance). Our analyses identified four unique pathways of traveling to the collective past from the election night based on these ratings. The resultant pathways mapped onto sociopolitical divides in age, voting behavior, party identification, religiosity and political orientation. These pathways revealed how certain ways of thinking of the past and the future offer psychological buffers against electoral loss. Specifically, processing the election protected future individual agency, and remembering an agentic, inclusive past scaffolded future political group agency. Our findings point to shared cognitive processes behind sociopolitical divides. Psychology collective mental time travel collective memory future projection election memory Figures Figure 1 Figure 2 Figure 3 Introduction In the last decade, there has been considerable research highlighting the links between thinking about the past and future both in the personal (see Schacter et al., 2017; Szpunar, 2010) and collective realms (Szpunar, P.M & Szpunar, K.K, 2016; Topcu & Hirst, 2022; Kashima et al., 2025). Research on what is tagged collective mental time travel has shown that collective memory and collective future thoughts are thematically linked (Öner & Gulgoz, 2020; Topcu & Hirst, 2020) and reflect sociopolitical divides (Hacıbektaşoğlu et al., 2023; Yamashiro & Roediger, 2019). While earlier work has focused on the valence of fluently generated future projections and a dominant dystopian collective perspective (Shrikanth et al., 2018; Yao et al, 2025), more recent research has focused on how cognitive, cultural and sociopolitical factors impact collective mental time travel to provide a more nuanced account (Hacibektasoglu et al., 2023; Mert, Hou & Wang, 2023; Mert & Wang, 2024; Oner & Gulgoz, 2020; Topcu & Hirst, 2024). In present research, using a unique data-driven exploratory approach, we investigated how retrieval of a presidential election cue retrieval of other collective past events and shape collective future projections and their characteristics. We argue that these recollections anchored to presidential elections help identify what we refer to as collective mental time travel pathways: clusters of particular past, present and future events that effectively capture nuances across sociopolitical identity. Finally, future projections across MTT pathways reveal coping mechanisms upon electoral win or defeat. Elections as Nexus Points We utilized the context of national elections to further investigate collective mental time travel processes. In many parts of the world, presidential elections have increased in perceived significance given deeply polarized societies. In recent years, numerous presidential or parliamentary elections have been characterized by polarized electoral campaigns tainted with mis/disinformation (e.g. Brazil 2022, Hungary 2022, Turkey 2023, Georgia 2024; France 2024, USA 2024, Germany 2025); some also led to anxiety-driven alliances (e.g. Hungary, France, Turkey, Georgia) and even to serious post-election protests (Jan 6 Riots in the US 1 ; 2022-2023 Brazil Election Protests 2 ; 2024 Georgia 3 ). We do not intend to merge the mentioned elections and discontents that gave rise to the protests and claim they are the same. However, we argue that certain characteristics of presidential elections make them ideal anchor points to study collective mental time travel, as they are highly salient, emotional and memorable collective events experienced by a majority of the population. Aside from being substantial nexus points for a nation in terms of determining her future, elections are emotionally charged events, both for the winners and the losers. Heightened emotional charge in important political events frequently end up as flashbulb memories, which are vivid and confident recollections of unexpected, consequential events (Brown & Kulik, 1977). Recent research has shown that group identity was a predictor in continued confidence and vividness of such flashbulb memories (Cyr, Toscano & Hirst, 2024; Talarico, Bohn & Wessel, 2019), despite longitudinal evidence noting discrepancies in recollections (Hirst et al, 2015). In a longitudinal study of 2016 American Presidential Election flashbulb memories, Chiew, Harris and Adcock (2022) found differences in memory across voter groups. As expected, winners (Trump supporters) reported highly positive responses, losers (Clinton supporters) reported highly negative responses, and the third party/nonvoters reported mildly negative responses. Regardless of election results, politically engaged Clinton and Trump supporters reported greater memory vividness and event importance, but vividness for activities and location, which are more in line with flashbulb memory characteristics, were specifically enhanced among Trump supporters. Losing the election led to higher levels of media consumption and social engagement with others in Clinton supporters and surprised individuals, particularly ones that showed high negative affect. Winning or losing an election has both political results on a collective level and psychological results on an individual level. On a political level, elections can contribute to consistent and long term polarization among groups, regardless of outcome (Iyengar et al, 2019; Fasching et al, 2024). On an individual level, elections can cause stress (Stanton et al, 2010; Early et al, 2023) and overall differences in wellbeing is found between winners and losers after an election, particularly for partisans (Toshkov & Mazepus, 2023). One way to mitigate this negative psychological outcome is “anticipatory coping”, whereby participants prepare for an event before it occurs, increasing feelings of control and well-being (Johnson & Neupert, 2025). Mental time travel allows one to picture plausible alternatives. Therefore, in the context of elections, engaging in this process might activate anticipatory coping mechanisms as people imagine unwanted outcomes and its impact. We know that losers of an election remain bitter in the long run (in Denmark, Hansen, Klemmensen & Serritzlew, 2019). But it is not merely losers who experience stress and deteriorated well-being. “Non-optimal winners”, those who voted for their second choice but won, remain closer to the losers (compared to the “optimal winners”) in post-election satisfaction with democracy (Singh, 2014). Simply put, the post election mindset is more complex that simply winning and losing. Based on literature, one can assume significant variation in how an election is remembered. However, research to date has not directly looked into how an election memory triggers events from the collective past and future. In the current study, we specifically aimed to identify if election memories along with the cued past events could trigger unique pathways into the collective future and whether through these pathways we could identify pathways of mental time travel within a nation, reflecting greater nuance than winners vs losers. Mental Time Travel and Agency Mental time travel refers to the ability to recall/relive past experiences and imagine/prelive future events (Tulving, 1985). Over the past two decades, research on episodic future thinking has expanded through various methodologies (Klein, 2013; Schacter et al., 2017; Szpunar, 2010). These findings align with the constructive episodic simulation hypothesis (Schacter & Addis, 2007), which suggests that future thinking is a creative process that reconstructs and recombines past experiences. What we remember, then, impacts what we imagine will happen. And this can happen not only at the individual level but also at the collective level (Merck et al., 2016; Szpunar & Szpunar, 2016; Topçu & Hirst, 2022; Yamashiro & Topçu, 2025). Remembering collective past serves many functions including creating and strengthening a collective identity, mitigating collective negative emotions, and guiding communities into the future (Uzer et al, 2024). Thus, shared representations of the past ties individuals together into a community, helps them cope in hard times, and prepares them for a future with the knowledge of what has been (Liu & Hilton, 2005). We expect to observe these in the context of a consequential and polarizing election at hand: we expect that remembering a shared representation of the past would bring some participants closer despite partisan animosities, help the losing side deal with the negative outcome, and prepare all for the future. Exactly how the participants will prepare for the future will depend on what they remember, as how individuals remember the collective past and imagine the collective future are tied: manipulating the valence of remembered collective events can influence the valence of imagined future events (Ionescu et al., 2024) and remembering the collective past through certain narrative templates increases the likelihood of using the same narrative templates when imagining the collective future (Topçu et al., in prep). As people identify with their countries more, view their society as less disintegrated, they imagine the country’s future to be more positive (Mert et al., 2023; Ionescu et al., 2022; Hazan et al., 2024). Thus, the more central their identity their group is (family or nation), people they view the future of that group in a more positive light (“centrality to self”; Berntsen & Rubin, 2024). Agency proves to be crucial here, as this centrality is associated with the degree of agency they attribute to themselves over country level-events (Berntsen & Rubin, 2024). Agency has various levels, ranging from individual to national, and both self- and nation-agency are related to the past and future collective event positivity (Topçu & Hirst, 2020; Topçu & Hirst, 2024). More importantly, people are relatively optimistic about the future: they attribute more agency to their nation and themselves over future collective events than past ones. Viewing one’s nation and themselves as more agentic in the future, then, paints a rosier future (Topçu & Hirst, 2020; Topçu et al., in prep). The concept of agency is especially critical in the context of national elections. Individuals rarely have a chance to influence collective events –reflected in the low-level self-agency scores (Berntsen & Rubin, 2024; Topçu & Hirst, 2020; Topçu & Hirst, 2024). Elections are probably the most salient contexts in which individuals have a sense of self-agency in deciding where the country is headed. That is one reason why elections can be considered as a critical nexus point which people can use to mentally travel to the collective past and future. In the collective future thinking literature, no study so far uses an event as a reference point to think about the past and imagine the future. As outlined above, we will treat the 2023 presidential elections in Turkey as an anchor for collective mental time travel. In doing so we aim to capture the narrative links people build between the past, present, and the future (Wertsch, 2002, 2021). In our exploration we will focus on factors that have been explored in previous studies through the evaluation of events in terms of their importance, valence, vividness, and agency. This allows us to integrate the literature on collective MTT connecting the past and the future through identifying the cognitive mechanisms based on event ratings. Current Study The presidential elections we utilize was one of the most consequential elections in Turkish history taking place on the centennial of the Republic. As the discontent from a failing economy and judicial system hinted at a possible government change after two decades of Erdogan rule, the opposition alliance once again lost, rendering any hope for change unlikely 4 . We chose to use this election as a temporal collective anchor, acting as a cue to guide retrieval and generation of similarly important collective past and future events and help us identify collective mental pathways and their characteristics. The mental time travel pathways reflect specific combinations of past event and election night ratings identified via factor analysis (see Defining Pathways). We first explored how these pathways diverge across meaningful sociopolitical divides (party identification, left/right, religious/secular). We then investigated how future projections in valence and agency differ as a factor of these mental time travel pathways. Taking this bottom-up approach provided a richer understanding of event-cued mental time travel at the collective level as opposed to looking solely at demographic or sociopolitical (eg.voting behavior) characteristics of participants. In what follows, we demonstrate four distinct mental time travel pathways that not only have meaningful differences in their level of support for each candidate, party identification and political orientation, but also the extent to which they focus on the election night (reflecting upon losing or glorifying upon winning) or (remembering recent or positive agentic) collective past. Method Participants This study was determined exempt by the BRANY IRB. We had a representative sample from Istanbul, Turkey’s most populous city (18.5% of the Turkish population; TUIK, 2021), collected by a polling company. Istanbul is usually reflective of the electoral trends in Turkey as evidenced in the parallels between election results in Turkey. Therefore, a representative dataset from Istanbul can represent main patterns in the country. The data was collected between September 30th-October 1st, 2023, 4 months after the second round of the presidential elections. The polling company reached a representative sample in line with EU Classification “Nomenclature of territorial units for statistics” ( Overview - NUTS - Nomenclature of Territorial Units for Statistics - Eurostat ) by geographically layering the sample in randomly selected districts of Istanbul, which receives within-country migration that makes the statistics on par with the country. As such, a minimum of 50 district quota was captured through making in person interviews in houses and workplaces. This allowed the geographical, socioeconomic and political diversity to be represented in our sample. We ended up with 402 participants. 46.7% of the participants voted for Kilicdaroglu, the opposition candidate in the second round of the elections, 44.9% voted for Erdogan, the incumbent president, and 8.4% did not vote. 51.1% of our sample was male, and 48.9 percent was female. As Erdogan won the election (52%), we believe the mismatch between our sample and the actual election results are a result of the tendency to respond to polls, which was evident in pre-election polling (Altunkaya, 2023). In terms of educational distribution, 0.7 percent of our sample did not have formal schooling, 31.3% were primary school graduates, 42.9% were high school graduates, 22.1% had university or community school degrees, and 3% had Masters or Phd degrees 5 . Our sample size is over the threshold for conducting a power analysis (Russell, 2002; Field, 2018). For the repeated measures ANOVA we undertook for future agency (3 levels), we undertook a power analysis after identifying 4 factors that would serve as between subjects variable. To detect a small effect size of .20 using Cohen's (1988) criteria, with a significance criterion of α = .05 and power = .95, the minimum sample size needed was N = 92 for an ANOVA with between within interaction. Thus, the obtained sample size of N = 379 is more than adequate to test the study hypothesis. As we have a representativeness concern, our sample size aims to optimize between being overpowered and being representative. Materials and Procedure Data and Open Science The data used in this study can be found at the OSF repository, https://osf.io/sv29c/?view_only=ab88f291fc714327b07388faaf41e964 . Evaluation of the Election After consenting to the survey, participants were asked to think back to when they first learned about the results of the second round of the 2023 Presidential elections. Gender-matched pollsters wrote down their brief responses to ensure participants thought about the election night, which included the details about the circumstances in which they learned about the election results. After that, participants rated the vividness and valence of their recollection on a scale of 1 to 5, 1 being not vivid at all, and 5 being very vivid. They then answered agency-related questions for individual, (“ How much do you think you as an individual and your actions shaped this event? ”), political group (“ How much do you think the political group you feel closest to shaped this event? ”), and national agency (“ How much do you think your nation shaped this event? ”), again on a scale of 1 to 5, 1 being not at all, and 5 being a lot. To assess the impact of the election further, we asked how much they followed the news then, compared to pre-election, and how much they talked about the election results with their close circle. They then rated the personal, national, international and generational importance of the presidential elections. Past and Future National Events In the next section, we counterbalanced the design such that participants either first mentally traveled to the collective past and then made a future projection, or vice versa. For the collective past task, they were asked to think back to the last 25 years and remember a national event as important as the 2024 election (“ Can you remember a collective event as important as the Presidential Elections of 2023 that happened in the past 25 years? What was that event ?”) For the future task, they were asked to project the next 25 years and imagine an event that would be as important as the 2024 election (“ Can you imagine a collective event as important as the Presidential Elections of 2023 that is likely to happen in the next 25 years? What is that event ?”). For both past and future events, participants rated valence, vividness, agency (individual, political group, nation) and importance (individual, national, international, generational) just like their responses for presidential elections. They were also asked to rate how similar the past and the future event was to the presidential election, and remember/estimate when the event happened/will happen. There was no effect of counterbalancing on any of the future variables. This test offers no problem in the future analyses, as we did not use international importance in our analyses. Scales After the mental time travel section, Need for Closure (NFC), System Justification (SJ, Collective Angst (CA) and Collective Nostalgia (CN) were measured. We used a short 15-item Need for Cognitive Closure Scale, scaled from 1 to 6 (Webster & Kruglanski, 1994; Roets & Van Hiel, 2007, Turkish adaptation by Seker & Akman, 2015), which broadly measures the need for certainty (“I dislike questions which could be answered in many different ways”). This inventory was found to be highly reliable (36 items; α = .72). In addition, participants filled out a 8-item System Justification Scale on a scale of 1 to 5 (Kay & Jost, 2005, Turkish adaptation by Yıldırım, 2010, α = .67), which assessed their attitudes about the status quo (“In general, Turkey is just and fair.”). The Collective Angst and Nostalgia scales were adopted from Smeekes et al. (2018)’s study, and included four items each. The scales contained items such as “I am worried about the future vitality of Turkey” for CA and “I get nostalgic when I think back of Turkey in past times” for CN. These scales were followed by demographic questions, which captured ideological divides like religiosity, left/right divide, secularism, patriotism, previous and current voting behavior, party identification, age, gender, SES, education and city of origin. See supplementary information for the full questionnaire in English. Results To identify the collective MTT pathways linking the election night, collective memories and collective future projections, we first conducted a factor analysis on event ratings for the election night and the collective past event . The characteristics of the factors, defined by the prominent event ratings, enabled us to identify the MTT pathways between the election night and the collective past event. We grouped each participant according to how well they fit into a particular factor (explained below), and checked if these pathways mapped onto the individual level sociopolitical differences. Lastly, using this event-based (election night and collective past) classification, we compared groups’ future projections. There are several novelties in our approach. First, we used factor analysis to identify shared features across election and past event recollections. This allowed us to identify common characteristics between responses even though people may have identified separate events. In essence, we used factor analysis to reduce the individual level event ratings into meaningful clusters of mental time travel pathways . This aligns with typical uses of factor analysis for data reduction (Russel, 2002). Second, we utilized pathways derived from event ratings and compared how individuals in different pathways projected the future, focusing on event characteristics that mapped onto individual differences in sociopolitical characteristics and demographics. In other words, unlike many studies looking at political contexts, we did not group participants based on demographics or sociopolitical identity, but rather on how people recalled election night and collective past. We present our findings under three sections: defining the pathways through factor analysis, understanding the pathways through sociopolitical characteristics, and utilizing the pathways in understanding different collective future imaginations. Defining Pathways: from Election Night to the Collective Past We conducted an exploratory factor analysis on ratings for the election night and the past event memories, using SPSS (version 30). Specifically, we included agency (individual, political group, nation), importance (individual, national, international, generational), valence and vividness ratings of both the election night and the past event, as well as how much participants followed the news right after the election, how much they talked to their close circle after the election, and the similarity between the election night and the subjective temporal distance between the election night and the past event in the analyses. After preliminary analyses, vividness of the past event and following the news after the election were dropped from the analysis as their communality scores were below .25 (Appendix A). We explain each one of the four factors in terms of prominent event ratings that characterize them below. We then identify a single best-fit factor for each participant, and describe the sociopolitical differences across the individuals whose mental time travel pathways are best represented by that particular factor. Factor 1: Election Reflection The first factor was characterized by high scores for election night importance on personal, generational and national levels, the vividness of the election night, how much the participants talked about the election night with their close circle, and the agency of the Turkish nation on the election night. Thus, the participants who are the best fit for this factor scored high on various measurements of importance of the election night, remembered it vividly, talked about the election night with their close circle, and believed that the Turkish nation had high agency on the election night. All points to reflecting on election night , so we will be referring to this factor as the election reflection pathway from now on. Factor 2: Recent Past Importance The second factor was characterized by high scores in importance of the past event on national, generational and personal levels, and the temporal distance between the election night and the past event. A negative correlation of temporal distance meant that a good fit for this factor was characterized by less temporal distance between the election night and the past event. Overall, participants who are a better fit for Factor 2 had high ratings on the importance of a past event that was closer to the present. Thus, this factor will be referred to as the Recent Past Importance pathway. Factor 3: Agentic Past Achievement The third factor was characterized by past agency , specifically past agency of the political group, individual, Turkish nation, and valence of the past event . Overall, this suggests that Factor 3 was characterized by positive past events that had high agency on individual, national, and political group level. Thus, this group will be referred to as Agentic Past Achievement pathway. Factor 4: Election Glorification The fourth factor was characterized by the valence of the election night , individual and political group agency at the election night as well as similarity between the election night and the past event. Thus, Factor 4 is characterized by a positive election night recollection with high individual and political group agency. The similarity variable had a negative loading, meaning, the past event differed from the election night in terms of similarity. This might be an optimistic way of distancing from a suboptimal past through a general election win. This factor will be referred to as the Election Glorification pathway. Table 1 . Pattern Matrix with Principal Axis Factoring Variables Election Reflection Recent Past Importance Agentic Past Achievement Election Glorification Election Night, Generational Importance .87 Election Night, Personal Importance .87 Election Night, National Importance .79 Election Night, International Importance .62 Election Night, Vividness .58 Election Night, Communication .54 Election Night, Turkish Nation Agency .51 Past Event, National Importance .90 Past Event, Generational Importance .89 Past Event, Personal Importance .87 Distance between Election and Past Event -.62 Past Event, Political Group Agency .83 Past Event, Individual Agency .82 Past Event, Valence .81 Past, Turkish Nation Agency .70 Election Night, Valence .89 Election Night, Individual Agency .86 Election Night, Political Group Agency .83 Similarity between Election and Past Event -.40 Understanding the Pathways: Sociopolitical Characteristics The factor scores were calculated by the regression method, which predicted the location of each individual on the factor with respect to standardized observed values of the items with a mean of 0 (DiStefano, Zhu, Mîndrilă, 2009). This led to 4 standardized factor scores for each participant, negative and positive. The highest factor coefficient was chosen for each participant, as the higher the coefficient, the higher the participant scored in the variables that contributed to that factor. However, there were some participants whose highest factor score was negative, suggesting they had negative correlations, and were not a good fit to any of the factors. They were excluded from the analyses (N = 23). Thus, the chosen factor could be described as the factor that is the best fit for the participant. In the end, Election Reflection factor had 71 participants (39 Female, 32 Male), Recent Past Importance factor had 105 participants (58 Female, 47 Male), Agentic Past Achievement factor had 86 participants (35 Female, 51 Male), and Election Glorification factor had 118 participants (51 Female, 67 Male). See Appendix B. Before explaining characteristics of participants in pathways, it’s imperative to highlight that these factors are derived from event characteristics like vividness, valence, importance ratings and agency scores for both election night and the past event. We did not include any demographic variables at any point, so the differences we find points to a successful parsing out via event characteristics that captured socio-political differences in collective MTT. Voting Behavior of Across Pathways As Table 2 conveys, pathways diverge in terms of voting behavior. Election Reflection and Recent Past Importance pathways mostly included opposition participants, Election Reflection more so than Recent Past Importance. The Agentic Past Achievement pathway is more balanced, as the participants who are in this MTT pathway are divided between the two candidates 6 . The Election Glorification pathway, on the other hand, overwhelmingly consisted of Erdogan supporters. We argue these distinctions offer an insight beyond binary winner/loser distinctions after an election. The proper “winners” are the election glorifiers, who open an optimistic page via the election with individual and political group agency on election night. The “losers” are participants in the Election Reflection and Recent Past Importance pathways. However, they diverge in the way they mentally travel from the election night to the past: the participants in the election reflection pathway are still processing and reflecting on the election , vividly remembering and talking about it with their close circle, all the while highlighting the agency of the nation and importance of the election night. The Recent Past Importance participants simply give an event from the recent past. The Agentic Past Achievement pathway, on the other hand, provides a heterogenous point of comparison where opposition and Erdogan voters converge: through a positive past high in individual, political group, and national agency. Table 2 . Voting Behavior across Pathways Pathway Vote in Round 2 Counts % of Dimension Election Reflection Kilicdaroglu 60 84.5% Erdogan 8 11.3% Other 3 4.2% Recent Past Importance Kilicdaroglu 70 66.7% Erdogan 22 20.9% Other 13 12.4% Agentic Past Achievement Kilicdaroglu 34 39.5% Erdogan 42 48.8% Other 10 11.6% Election Glorification Kilicdaroglu 5 4.2% Erdogan 108 91.6% Other 5 4.2% See Table 3 for how demographic, sociopolitical and psychological measures (system justification, collective nostalgia, collective angst) vary across MTT pathways. To this end, we conducted one way ANOVAs with each of the variables as the dependent variable, and the best fit pathway as independent variable. We provide a summary table highlighting differences between pathways, and present the full set of statistical results in Appendix C. Table 3 . Characteristics of Pathways. Pathways go from opposition heavy to pro-Erdogan from left to right. Mean is reported in parentheses. Election Reflection Recent Past Importance Agentic Past Achievement Election Glorification Age - ( 37.7 ) Younger ( 36.2 ) Older ( 41.5 ) Older ( 42.6 ) Party Identification More ( 4.14 ) Less ( 3.68 ) - ( 4.0 ) - ( 4.04 ) Left/right Left ( 1.94 ) Left ( 2.07 ) Right ( 3.16 ) Most Right ( 4.32 ) Religious/secular Least ( 2.15 ) Least ( 1.21 ) Less ( 2.56 ) Most ( 3.09 ) Emotional Response More ( 2.85 ) Less ( 2.79 ) - ( 2.44 ) - ( 1.91 ) Economic Impact Worst ( -1.55 ) Worse ( -.44 ) Worse ( -.29 ) Best (. 46 ) System Justification Less ( 2.26 ) More ( 2.47 ) More ( 2.88 ) Most ( 3.28 ) Collective Anxiety Most ( 4.43 ) Most ( 4.30 ) More ( 3.58 ) Least ( 3.0 ) Collective Nostalgia Most ( 4.16 ) More ( 3.80 ) More ( 3.59 ) Least ( 3.11 ) Note. Due to a large number of pairwise comparisons, we denoted the hierarchy among the pathways as Most, More, Less, Least. The sign “-” means that there is no significant pairwise comparison with that pathway. The average scores are reported in parentheses. Except for economic impact rated between -2 to +2, all other ratings were from 1 to 5. All pairwise comparisons are corrected for multiple comparisons. Pathways divide on the left-right axis: Election Reflection and Recent Past Importance pathways are significantly more left wing, while Agentic Past Achievement and election glorifying pathways are more right wing. Agentic Past Achievement and Election Glorification pathways further differentiate in terms of religion and future economic expectation: election glorifiers are more religious and optimistic than participants in Agentic Past Achievement pathway. Even though Election Reflection and Recent Past Importance participants are both left-wing, less religious and opposition heavy, they differed in party identification and emotional response to election. Specifically, participants in Recent Past Importance pathway identify with their party less and report being less emotionally affected than participants in the Election Reflection group. Utilizing the Pathways: Differences in Future Event Characteristics Upon defining and understanding the pathways derived from event ratings of the election and an equally important collective past event, we now report findings on future projections across pathways. Future Event Valence Future event valence differed across pathways, Welch’s F (3, 194.61) = 10.84, p < .001, partial η 2 = .08. All post hoc comparisons were significant with the negativity of the future events increasing from Election Glorifying ( M = -.24, CI [-.53, .05]), Agentic Past ( M = -.15, CI [-.49, .19]), Recent Past Importance ( M = -1.18, CI [-1.49, -.87]) and Election Reflection ( M = -1.01, CI [-1.39, -.64]), post hoc tests: t (159.65) = -3.21, p = .009, d = .48, t (154.15) = -3.29, p = .007, d = .54, t (160.81) = -4.45, p < .001, d = .64, t (219.06) = -4.54, p < .001, d = .59. Not surprisingly, losing the election led to a more negative future for those on the losing side, except for the losers in the agentic past achievement pathway. However, the outlook was negative overall. Future Event Agency How did MTT pathways differ in future agency? To understand this, we conducted a 3X4 repeated measures ANOVA, where the agency rating of the event (individual, national, political group) was the within subjects variable, and the MTT pathway was the between subjects variable. There was a main effect of agency, F (2, 752) = 201.6, p < .001, partial η 2 = .35, where across all pathways, national agency was the highest ( M = 3.47, CI [3.32, 3.61]), followed by political group ( M = 2.92, CI [2.76, 3.08]), and individual ( M = 1.98, CI [1.83, 2.12]) agency. More importantly, this agency pattern differed across MTT pathways, F (6, 752) = 7.42, p < .001, partial η 2 = .06. (Figure 4). The higher national agency over political group agency pattern disappeared for opposition pathways. For the Election Reflection and Recent Past Importance pathways, future national agency (Election Reflection: M = 3.28, CI [2.96, 3.61], Recent Past Importance: M = 3.57, CI [3.30, 3.84]) was higher than future political group agency (Election Reflection: M = 2.49, CI [2.13, 2.86], Recent Past Importance: M = 2.47, CI [2.17, 2.77]), t (376) = 4.66, ptukey < .001, d = .54, t (376) = 7.94, ptukey < .001, d = .68. There were no differences for Agentic Past Achievement and Election Glorification pathways. This can be understood as the effect of winning (vs. losing) an election. While losing an election is detrimental to the political group agency, winning leads to a political group agency that is on par with national agency. This is understandable, as winning an election gives a political party the power to determine the nation’s future for a limited time. However, despite almost 50% voting for the losing candidate, participants in the Agentic Past Achievement pathway maintained a high political group agency on par with those in the Election Glorification pathway. One might argue that this higher political group agency was a virtue of combining both the winners and the losers in the Agentic Past Achievement pathway, as political group agency in this pathway differed as a factor of voting behavior, t (74) = 2.18, p = .03, d = .50. Winners in the Agentic Past Achievement pathway indeed had higher political group agency ( M = 3.88, CI [4.33, 3.43]) than losers in the same pathway ( M = 3.12, CI [3.68, 2.56]). However, the political and the national agency of the losers in the agentic past achievement pathway did not differ, M = 3.44, CI [2.91, 3.97]), t (33) = 1.82, p = .08. Thus, the pattern of future political agency not suffering for the Agentic Past Achievement factor held true across voting behavior. Further, the future political agency of the losers in the Agentic Past Achievement pathway was still higher than the future political agency of opposition heavy Election Reflection ( M = 2.49, CI [2.13, 2.86]) and Recent Past Importance ( M = 2.47, CI [2.17, 2.77]) pathways. This is further proof that we are capturing a distinct mental time travel pathway than what would have been captured by simple voting behavior. What might be the reason for the resilience of the agentic past achievement pathway? Note that they were remembering a positive past event that the nation, as well as their political group had high agency over. This stop at an agentic, positive collective past seems to be driving a more positive (described in the previous section) and agentic future. Although we focus on mental time travel and its effects on a collective level, individual future agency is important in the way people engage with the collective. It is also important in how individuals cope after the elections are over and go on to their daily routine. We observed a divergence in the future individual agency of the two opposition heavy pathways: Recent Past Importance ( M = 1.53, CI [1.26, 1.80]) scored lower than Agentic Past Achievement ( M = 2.24, CI [1.95, 2.56]) and Election Glorification ( M = 2.35, CI [2.09, 2.60]), t (376) = 3.47, ptukey = .03, d = .51, t (376) = 4.31, ptukey = .001, d = .58. However, the future individual agency of the other opposition-heavy pathway, Election Reflection pathway, was on par with mixed Agentic Past Achievement and pro-Erdogan Election Glorifiers. Considering the Recent Past Importance pathway had lower party identification and less emotional response to the election than the Election Processors, we speculate that party identification is preventing resignation, and offering a buffer against a steep loss of future individual agency even in the face of a political defeat. Here, we observe two possible mitigation strategies upon losing an election: First, remembering a positive, agentic (national and political group) past protects future political group agency . Second, party identification buffers the loss of future individual agency . We argue that we can observe two pathway specific future agency buffers in the face of a substantial defeat: remembering a past where the political group, and the nation as a whole had agency (for future political agency) and party identification (for future individual agency). Discussion In this study, using an event-ratings-based categorization, we identified four divergent collective mental pathways. Our approach highlights that memories of the past cued by a consequential election help retrieve equally vivid and important collective future projections (Appendix D) that vary in valence and agency. We demonstrated that the collective MTT pathways captured nuance beyond winner and loser voter groups, accounting for demographic (age, left-right, religiosity, party identification), motivational and emotional (system justification, collective nostalgia, collective angst) differences. Our approach is unique in how it uses a widely experienced political event (presidential elections) as a collective temporal anchor to reveal insights into collective MTT and sociopolitical leanings. Our findings go beyond illustrating thematic overlap between collective past and future to capture variations in sociopolitical identities and future simulations. Specifically, our data shows the complex interaction between various aspects of what is collectively remembered and the kind of future it evokes. First, high party identification buffered the loss of future individual agency, despite not providing a rosier future. The literature on election stress and wellbeing highlights “anticipatory coping”, which is preparing for an event before it occurs, increasing feelings of control and wellbeing. MTT into the future, then, emerges as a way to cope with post-election dip in psychological wellbeing. Thus, we propose that reflecting on the election upon losing, characterized by talking to close others about it, acknowledging its importance and accepting it as the will of the nation is a way of healthy coping. It leads to a negative future, but one with higher individual agency. The key for this pathway seems to be party identification. In the end, psychological wellbeing at the individual level is connected to party identification on the social level. Second, we found that some members of a nation come together in how they remember the past and project a future. They remember a positive agentic past where both their political group and nation had an effect, and in turn they projected a rosier and more agentic future- both in terms of political group and national agency. In his attempt to understand what transforms a body of people into a nation, Anderson (1983) coined the term “imagined communities”. Defining a nation as a social construct rather than a natural entity, he argues that because one can not simply know all of the members of their nation, one fills in the gap with their imagination. Taking Anderson’s definition of a constructed nation, we argue that we are capturing an imagination as a nation in this pathway. This has reflections in collective memory literature, in schematic narrative templates of a nation (Wertsch, 2021) that ascend generations and shapes collective thinking (e.g. US as the city on a hill), and in the Turkish case, stable dimensions of collective memory even after a coup attempt (Mutlutürk et al., 2022). We argue that this methodology of focusing on event based mental time travel pathways as opposed to voting behavior can help understand the nation as a whole, but heterogeneous entity. While we acknowledge that our sample does not have perfect representation, our approach allows us to achieve nuance nevertheless. One possible future venue of utilizing this methodology would ask if evoking a particular collective memory can manipulate the particular mental time travel pathway an individual takes “naturally”. Probing if we can switch the natural pathways found in this representative and ecologically valid data would be crucial for various interventions. Extant literature suggests that this manipulation works with valence (Ionescu et al, 2024), and future work might tackle switching pathways after an electoral defeat. Finally, although our results take a snapshot after a consequential election, future work needs to tackle the dynamic nature of collective representations, and identify if mental time travel pathways derived after various consequential events reflect a similar pattern. Validating this methodology across different cultures and political contexts is crucial. We know that people in Western societies usually exhibit a positivity bias for the personal past and a negativity bias for the collective past (Shrikanth & Szpunar, 2021), as well as for personal and collective future (Mert & Wang, 2024; Shrikanth et al., 2018; Yamashiro & Roediger, 2019). Chinese people, on the other hand, do not (Deng et al., 2023; Mert et al., 2023; see Wang & Mert, 2025 for a review). Testing mental time travel pathways across non-Turkish samples might unearth how subgroups within a nation create different imaginations, which would help build efficient communication strategies to combat possible downfalls arising from this divergence. References Altunkaya, T. (2023, April 19). Turkey opinion poll tracker: Erdoğan vs Kılıçdaroğlu. Euronews . https://www.euronews.com/2023/03/14/turkey-opinion-poll-tracker-erdogan-vs-kilicdaroglu Anderson, B. (1983). Imagined Communities: Reflections on the Origin and Spread of Nationalism. London: Verso. Berntsen, D., & Rubin, D. C. 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The complex act of projecting oneself into the future. Wiley Interdisciplinary Reviews: Cognitive Science , 4 (1), 63-79. Liu, J. H., & Hilton, D. J. (2005). How the past weighs on the present: Social representations of history and their role in identity politics. British Journal of Social Psychology , 44 (4), 537-556. Merck, C., Topcu, M. N., & Hirst, W. (2016). Collective mental time travel: Creating a shared future through our shared past. Memory Studies , 9 (3), 284-294. Mert, N., Hou, Y., & Wang, Q. (2023). What lies ahead of us? Collective future thinking in Turkish, Chinese, and American adults. Memory & Cognition , 51 (3), 773-790. Mert, N., & Wang, Q. (2024). Valence and perceived control in personal and collective future thinking: the relation to psychological well-being. Cognition and Emotion , 38 (5), 675-690. Mutlutürk, A., Tekcan, A. I., & Boduroglu, A. (2022). Stability and change in the organisation of collective memory representations. Memory, 30(10), 1302-1318. Overview - NUTS - Nomenclature of territorial units for statistics - Eurostat. (n.d.). Eurostat. https://ec.europa.eu/eurostat/web/nuts Öner, S., & Gülgöz, S. (2020). Representing the collective past: Public event memories and future simulations in Turkey. Memory , 28 (3), 386-398. Russell, D. W. (2002). In search of underlying dimensions: The use (and abuse) of factor analysis in Personality and Social Psychology Bulletin. Personality and social psychology bulletin , 28 (12), 1629-1646. Schacter, D. L., & Addis, D. R. (2007). On the constructive episodic simulation of past and future events. Behavioral and Brain Sciences , 30 (3), 331-332. Schacter, D. L., Benoit, R. G., & Szpunar, K. K. (2017). Episodic future thinking: Mechanisms and functions. Current opinion in behavioral sciences , 17 , 41-50. Seker, B. D., & Akman, E. (2015). Bilişsel Kapalılık İhtiyacı Ölçeğinin Türkçeye Uyarlanması: Güvenirlik ve Geçerlik Analizi. Turk Psikoloji Yazilari, 18(35), 51. Shrikanth, S., Szpunar, P. M., & Szpunar, K. K. (2018). Staying positive in a dystopian future: A novel dissociation between personal and collective cognition. Journal of Experimental Psychology: General, 147(8), 1200. Shrikanth, S., & Szpunar, K. K. (2021). The good old days and the bad old days: Evidence for a valence-based dissociation between personal and public memory. Memory , 29 (2), 180-192. Singh, S. P. (2014). Not all election winners are equal: Satisfaction with democracy and the nature of the vote. European Journal of Political Research , 53 (2), 308-327. Stanton, S. J., LaBar, K. S., Saini, E. K., Kuhn, C. M., & Beehner, J. C. (2010). Stressful politics: Voters’ cortisol responses to the outcome of the 2008 United States presidential election. Psychoneuroendocrinology , 35 (5), 768-774. Szpunar, K. K. (2010). Episodic future thought: An emerging concept. Perspectives on Psychological Science , 5 (2), 142-162. Szpunar, P. M., & Szpunar, K. K. (2016). Collective future thought: Concept, function, and implications for collective memory studies. Memory Studies, 9(4), 376-389. Talarico, J. M., Bohn, A., & Wessel, I. (2019). The role of event relevance and congruence to social groups in flashbulb memory formation. Memory , 27 (7), 985-997. Topcu, M. N., & Hirst, W. (2020). Remembering a nation’s past to imagine its future: The role of event specificity, phenomenology, valence, and perceived agency. Journal of Experimental Psychology: Learning, Memory, and Cognition , 46 (3), 563. Topcu, M. N., & Hirst, W. (2022). Collective mental time travel: Current research and future directions. Progress in brain research, 274(1), 71-97. Topçu, M. N., & Hirst, W. (2024). When the personal and the collective intersects: Memory, future thinking, and perceived agency during the COVID-19 pandemic. Journal of Experimental Psychology: General , 153 (9), 2258. Toshkov, D., & Mazepus, H. (2023). Does the election winner–loser gap extend to subjective health and well-being?. Political Studies Review , 21 (4), 783-800. Tulving, E. (1985). How many memory systems are there?. American psychologist , 40 (4), 385. TÜİK Kurumsal . (2021, February). Retrieved February 15, 2025, from https://data.tuik.gov.tr/Bulten/Index?p=Adrese-Dayali-Nufus-Kayit-Sistemi-Sonuclari-2020-37210 TÜİK Kurumsal . (2023, May 26). Retrieved from https://data.tuik.gov.tr/Bulten/Index?p=Ulusal-Egitim-Istatistikleri-2022-49756 Uzer, T., Akdağ, S., Dalmış, T., Özdemir, T. V., Demirtaşoğlu, D., Hekimci, İ., ... & Şenyurt, S. (2024). Measuring functions of remembering public events: Development of a functions of collective memory questionnaire. Applied Cognitive Psychology , 38 (3), e4213. Wang, Q., & Mert, N. (2025). Collective future thinking at a time of geopolitical tension. Trends in Cognitive Sciences . Wertsch, J. V. (2002). Voices of collective remembering . Cambridge University Press. Wertsch, J. V. (2021). How nations remember: A narrative approach. Oxford University Press. Yamashiro, J. K., & Roediger III, H. L. (2019). How we have fallen: Implicit trajectories in collective temporal thought. Memory, 27(8), 1158-1166. Yao, Z., Multhaup, K. S., & Salter, P. S. (2025). Valence-based biases in collective temporal thought: The role of question framing, culture, and age. Memory & Cognition, 1-16. Footnotes https://www.bbc.com/news/world-us-canada-56004916 https://en.wikipedia.org/wiki/2022%E2%80%932023_Brazilian_election_protests https://www.bbc.com/news/articles/cwy5ypkn7kjo https://www.bbc.com/news/world-europe-65743031 Turkish Institute of Statistics report has 7.5% without formal education, 22.7% primary school graduates, 22.7 middle school graduates, 23.2% high school graduates, and 23.9% with university or higher education degree (TUIK, 2023) The mixed voting behavior in the Agentic Past Achievement is curious due to 20 + years of polarization. To this end, we looked if the participants in this pathway ever voted for Erdogan. The results were a clean 50/50, where 50% of them previously voted for Erdogan at least once. All of the post-hoc tests reported are Games-Howell tests, unless it is reported as Tukey’s. Additional Declarations The authors declare no competing interests. Supplementary Files Appendix.docx 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. 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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-6789456","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":464479919,"identity":"5dfa907d-8699-450e-b0d0-5ef2ca3a423b","order_by":0,"name":"Elif Sozer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYDACdgglJwEieYjSwgyhjEnXkjiDaC38zOwPH/6ouJc+c0YC44O3bURokWzmMTaQOFOcO1sigdlwLjFaDA7zsEkYtiXkzpNIYJPmJUaL/WH2ZxKJ/xLS5SQS2H8TpcWAmcFM4mBDQoI00BZmorRIHOYxNmw4lmA4s+dhs+Scc0Ro4W9vB4ZYTYK8xPHkgx/elBGhBQkwNpCmfhSMglEwCkYBbgAAWb8upOcPZG4AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-5121-2685","institution":"Koc University","correspondingAuthor":true,"prefix":"","firstName":"Elif","middleName":"","lastName":"Sozer","suffix":""},{"id":464479920,"identity":"8621a892-c8ae-40d9-bee4-87ee46369a2a","order_by":1,"name":"Meymune Topcu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Meymune","middleName":"","lastName":"Topcu","suffix":""},{"id":464479921,"identity":"5293495d-3581-4acc-8f1c-308b60e99ea1","order_by":2,"name":"Aysecan Boduroglu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Aysecan","middleName":"","lastName":"Boduroglu","suffix":""}],"badges":[],"createdAt":"2025-05-31 07:48:35","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6789456/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6789456/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83905439,"identity":"27673b05-b71d-4c01-84fd-27bd75a5618f","added_by":"auto","created_at":"2025-06-04 10:13:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":97688,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eProcedural Timeline of the Experiment.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. Participants were randomly assigned to either generate a collective past or collective future event first. There were no differences as a factor of counterbalancing.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6789456/v1/6095bb9b827cc3bddf78b5dc.png"},{"id":83902875,"identity":"e62c26bf-ff91-43cb-bf42-e28913ec2ca9","added_by":"auto","created_at":"2025-06-04 09:49:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFuture Event Valence across Pathways. Error bars represent 95% Confidence Intervals.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6789456/v1/f828dd91f7069a0b5f5d3f3a.png"},{"id":83904117,"identity":"8e6aafaa-1259-4d1b-b28c-e5f03a294dd8","added_by":"auto","created_at":"2025-06-04 09:57:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":150768,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFuture Event Agency across Pathways. Error bars represent 95% Confidence Interval\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6789456/v1/9d673da5c660a30492ee7a93.png"},{"id":83905962,"identity":"de11c1fc-1caa-426a-a327-cb687b67e20e","added_by":"auto","created_at":"2025-06-04 10:21:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1346439,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6789456/v1/bf63c7e9-4ca1-429f-b1dd-db851cef5143.pdf"},{"id":83902878,"identity":"37705ffc-bed9-4cd2-8076-8eb02fee0912","added_by":"auto","created_at":"2025-06-04 09:49:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":228901,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-6789456/v1/6bb2323411212aa1837af3e0.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003ch6\u003eBeyond Winners and Losers: Collective Mental Time Travel Pathways Buffer Future Agency after Elections\u003c/h6\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn the last decade, there has been considerable research highlighting the links between thinking about the past and future both in the personal (see Schacter et al., 2017; Szpunar, 2010) and collective realms (Szpunar, P.M \u0026amp; Szpunar, K.K, 2016; Topcu \u0026amp; Hirst, 2022; Kashima et al., 2025). Research on what is tagged collective mental time travel has shown that collective memory and collective future thoughts are thematically linked (\u0026Ouml;ner \u0026amp; Gulgoz, 2020; Topcu \u0026amp; Hirst, 2020) and reflect sociopolitical divides (Hacıbektaşoğlu et al., 2023; Yamashiro \u0026amp; Roediger, 2019). While earlier work has focused on the valence of fluently generated future projections and a dominant dystopian collective perspective (Shrikanth et al., 2018; Yao et al, 2025), more recent research has focused on how cognitive, cultural and sociopolitical factors impact collective mental time travel to provide a more nuanced account (Hacibektasoglu et al., 2023; Mert, Hou \u0026amp; Wang, 2023; Mert \u0026amp; Wang, 2024; Oner \u0026amp; Gulgoz, 2020; Topcu \u0026amp; Hirst, 2024). In present research, using a unique data-driven exploratory approach, we investigated how retrieval of a presidential election cue retrieval of other collective past events and shape collective future projections and their characteristics. We argue that these recollections anchored to presidential elections help identify what we refer to as collective mental time travel pathways: clusters of particular past, present and future events that effectively capture nuances across sociopolitical identity. Finally, future projections across MTT pathways reveal coping mechanisms upon electoral win or defeat.\u003c/p\u003e\n\u003ch2\u003eElections as Nexus Points\u003c/h2\u003e\n\u003cp\u003eWe utilized the context of national elections to further investigate collective mental time travel processes. In many parts of the world, presidential elections have increased in perceived significance given deeply polarized societies. In recent years, numerous presidential or parliamentary elections have been characterized by polarized electoral campaigns tainted with mis/disinformation (e.g. Brazil 2022, Hungary 2022, Turkey 2023, Georgia 2024; France 2024, USA 2024, Germany 2025); some also led to anxiety-driven alliances (e.g. Hungary, France, Turkey, Georgia) and even to serious post-election protests (Jan 6 Riots in the US\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e1\u003c/sup\u003e; 2022-2023 Brazil Election Protests\u003ca href=\"#_ftn2\" name=\"_ftnref2\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e2\u003c/sup\u003e; 2024 Georgia\u003ca href=\"#_ftn3\" name=\"_ftnref3\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e3\u003c/sup\u003e). We do not intend to merge the mentioned elections and discontents that gave rise to the protests and claim they are the same. However, we argue that certain characteristics of presidential elections make them ideal anchor points to study collective mental time travel, as they are highly salient, emotional and memorable collective events experienced by a majority of the population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAside from being substantial nexus points for a nation in terms of determining her future, elections are emotionally charged events, both for the winners and the losers. Heightened emotional charge in important political events frequently end up as flashbulb memories, which are vivid and confident recollections of unexpected, consequential events (Brown \u0026amp; Kulik, 1977). Recent research has shown that group identity was a predictor in continued confidence and vividness of such flashbulb memories (Cyr, Toscano \u0026amp; Hirst, 2024; Talarico, Bohn \u0026amp; Wessel, 2019), despite longitudinal evidence noting discrepancies in recollections (Hirst et al, 2015). In a longitudinal study of 2016 American Presidential Election flashbulb memories, Chiew, Harris and Adcock (2022) found differences in memory across voter groups. As expected, winners (Trump supporters) reported highly positive responses, losers (Clinton supporters) reported highly negative responses, and the third party/nonvoters reported mildly negative responses. Regardless of election results, politically engaged Clinton and Trump supporters reported greater memory vividness and event importance, but vividness for activities and location, which are more in line with flashbulb memory characteristics, were specifically enhanced among Trump supporters. Losing the election led to higher levels of media consumption and social engagement with others in Clinton supporters and surprised individuals, particularly ones that showed high negative affect.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWinning or losing an election has both political results on a collective level and psychological results on an individual level. On a political level, elections can contribute to consistent and long term polarization among groups, regardless of outcome (Iyengar et al, 2019; Fasching et al, 2024). On an individual level, elections can cause stress (Stanton et al, 2010; Early et al, 2023) and overall differences in wellbeing is found between winners and losers after an election, particularly for partisans (Toshkov \u0026amp; Mazepus, 2023). One way to mitigate this negative psychological outcome is \u0026ldquo;anticipatory coping\u0026rdquo;, whereby participants prepare for an event before it occurs, increasing feelings of control and well-being (Johnson \u0026amp; Neupert, 2025).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMental time travel allows one to picture plausible alternatives. Therefore, in the context of elections, engaging in this process might activate anticipatory coping mechanisms as people imagine unwanted outcomes and its impact. We know that losers of an election remain bitter in the long run (in Denmark, Hansen, Klemmensen \u0026amp; Serritzlew, 2019). But it is not merely losers who experience stress and deteriorated well-being. \u0026ldquo;Non-optimal winners\u0026rdquo;, those who voted for their second choice but won, remain closer to the losers (compared to the \u0026ldquo;optimal winners\u0026rdquo;) in post-election satisfaction with democracy (Singh, 2014). Simply put, the post election mindset is more complex that simply winning and losing.\u003c/p\u003e\n\u003cp\u003eBased on literature, one can assume significant variation in how an election is remembered. However, research to date has not directly looked into how an election memory triggers events from the collective past and future. In the current study, we specifically aimed to identify if election memories along with the cued past events could trigger unique pathways into the collective future and whether through these pathways we could identify pathways of mental time travel within a nation, reflecting greater nuance than winners vs losers.\u003c/p\u003e\n\u003ch2\u003eMental Time Travel and Agency\u003c/h2\u003e\n\u003cp\u003eMental time travel refers to the ability to recall/relive past experiences and imagine/prelive future events (Tulving, 1985). Over the past two decades, research on episodic future thinking has expanded through various methodologies (Klein, 2013; Schacter et al., 2017; Szpunar, 2010). These findings align with the constructive episodic simulation hypothesis (Schacter \u0026amp; Addis, 2007), which suggests that future thinking is a creative process that reconstructs and recombines past experiences. What we remember, then, impacts what we imagine will happen. And this can happen not only at the individual level but also at the collective level (Merck et al., 2016; Szpunar \u0026amp; Szpunar, 2016; Top\u0026ccedil;u \u0026amp; Hirst, 2022; Yamashiro \u0026amp; Top\u0026ccedil;u, 2025).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRemembering collective past serves many functions including creating and strengthening a collective identity, mitigating collective negative emotions, and guiding communities into the future (Uzer et al, 2024). Thus, shared representations of the past ties individuals together into a community, helps them cope in hard times, and prepares them for a future with the knowledge of what has been (Liu \u0026amp; Hilton, 2005). We expect to observe these in the context of a consequential and polarizing election at hand: we expect that remembering a shared representation of the past would bring some participants closer despite partisan animosities, help the losing side deal with the negative outcome, and prepare all for the future.\u003c/p\u003e\n\u003cp\u003eExactly \u003cem\u003ehow\u003c/em\u003e the participants will prepare for the future will depend on what they remember, as how individuals remember the collective past and imagine the collective future are tied: manipulating the valence of remembered collective events can influence the valence of imagined future events (Ionescu et al., 2024) and remembering the collective past through certain narrative templates increases the likelihood of using the same narrative templates when imagining the collective future (Top\u0026ccedil;u et al., in prep). As people identify with their countries more, view their society as less disintegrated, they imagine the country\u0026rsquo;s future to be more positive (Mert et al., 2023; Ionescu et al., 2022; Hazan et al., 2024). Thus, the more central their identity their group is (family or nation), people they view the future of that group in a more positive light (\u0026ldquo;centrality to self\u0026rdquo;; Berntsen \u0026amp; Rubin, 2024). Agency proves to be crucial here, as this centrality is associated with the degree of agency they attribute to themselves over country level-events (Berntsen \u0026amp; Rubin, 2024). Agency has various levels, ranging from individual to national, and both self- and nation-agency are related to the past and future collective event positivity (Top\u0026ccedil;u \u0026amp; Hirst, 2020; Top\u0026ccedil;u \u0026amp; Hirst, 2024). More importantly, people are relatively optimistic about the future: they attribute more agency to their nation and themselves over future collective events than past ones. Viewing one\u0026rsquo;s nation and themselves as more agentic in the future, then, paints a rosier future (Top\u0026ccedil;u \u0026amp; Hirst, 2020; Top\u0026ccedil;u et al., in prep).\u003c/p\u003e\n\u003cp\u003eThe concept of agency is especially critical in the context of national elections. Individuals rarely have a chance to influence collective events \u0026ndash;reflected in the low-level self-agency scores (Berntsen \u0026amp; Rubin, 2024; Top\u0026ccedil;u \u0026amp; Hirst, 2020; Top\u0026ccedil;u \u0026amp; Hirst, 2024). Elections are probably the most salient contexts in which individuals have a sense of self-agency in deciding where the country is headed. That is one reason why elections can be considered as a critical nexus point which people can use to mentally travel to the collective past and future.\u003c/p\u003e\n\u003cp\u003eIn the collective future thinking literature, no study so far uses an event as a reference point to think about the past and imagine the future. As outlined above, we will treat the 2023 presidential elections in Turkey as an anchor for collective mental time travel. In doing so we aim to capture the narrative links people build between the past, present, and the future (Wertsch, 2002, 2021). In our exploration we will focus on factors that have been explored in previous studies through the evaluation of events in terms of their importance, valence, vividness, and agency. This allows us to integrate the literature on collective MTT connecting the past and the future through identifying the cognitive mechanisms based on event ratings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCurrent Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe presidential elections we utilize was one of the most consequential elections in Turkish history taking place on the centennial of the Republic. As the discontent from a failing economy and judicial system hinted at a possible government change after two \u0026nbsp;decades of Erdogan rule, the opposition alliance once again lost, rendering any hope for change unlikely\u003ca href=\"#_ftn4\" name=\"_ftnref4\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e4\u003c/sup\u003e. We chose to use this election as a temporal collective anchor, acting as a cue to guide retrieval and generation of similarly important collective past and future events and help us identify collective mental pathways and their characteristics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mental time travel pathways reflect specific combinations of past event and election night ratings identified via factor analysis (see Defining Pathways). We first explored how these pathways diverge across meaningful sociopolitical divides (party identification, left/right, religious/secular). We then investigated how future projections in valence and agency differ as a factor of these mental time travel pathways. Taking this bottom-up approach provided a richer understanding of event-cued mental time travel at the collective level as opposed to looking solely at demographic or sociopolitical (eg.voting behavior) characteristics of participants. In what follows, we demonstrate four distinct mental time travel pathways that not only have meaningful differences in their level of support for each candidate, party identification and political orientation, but also the extent to which they focus on the election night (reflecting upon losing or glorifying upon winning) or (remembering recent or positive agentic) collective past.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was determined exempt by the BRANY IRB. We had a representative sample from Istanbul, Turkey\u0026rsquo;s most populous city (18.5% of the Turkish population; TUIK, 2021), collected by a polling company. Istanbul is usually reflective of the electoral trends in Turkey as evidenced in the parallels between election results in Turkey. Therefore, a representative dataset from Istanbul can represent main patterns in the country. The data was collected between September 30th-October 1st, 2023, 4 months after the second round of the presidential elections. The polling company reached a representative sample in line with EU Classification \u0026ldquo;Nomenclature of territorial units for statistics\u0026rdquo; (\u003cem\u003eOverview - NUTS - Nomenclature of Territorial Units for Statistics - Eurostat\u003c/em\u003e) by geographically layering the sample in randomly selected districts of Istanbul, which receives within-country migration that makes the statistics on par with the country. As such, a minimum of 50 district quota was captured through making in person interviews in houses and workplaces. This allowed the geographical, socioeconomic and political diversity to be represented in our sample. We ended up with 402 participants. 46.7% of the participants voted for Kilicdaroglu, the opposition candidate in the second round of the elections, 44.9% voted for Erdogan, the incumbent president, and 8.4% did not vote. 51.1% of our sample was male, and 48.9 percent was female. As Erdogan won the election (52%), we believe the mismatch between our sample and the actual election results are a result of the tendency to respond to polls, which was evident in pre-election polling (Altunkaya, 2023). In terms of educational distribution, 0.7 percent of our sample did not have formal schooling, 31.3% were primary school graduates, 42.9% were high school graduates, 22.1% had university or community school degrees, and 3% had Masters or Phd degrees\u003csup\u003e\u003csup\u003e5\u003c/sup\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOur sample size is over the threshold for conducting a power analysis (Russell, 2002; Field, 2018). For the repeated measures ANOVA we undertook for future agency (3 levels), we undertook a power analysis after identifying 4 factors that would serve as between subjects variable. To detect a small effect size of .20 using Cohen\u0026apos;s (1988) criteria, with a significance criterion of \u0026alpha; = .05 and power = .95, the minimum sample size needed was N = 92 for an ANOVA with between within interaction. Thus, the obtained sample size of N = 379 is more than adequate to test the study hypothesis. As we have a representativeness concern, our sample size aims to optimize between being overpowered and being representative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData and Open Science\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study can be found at the OSF repository, https://osf.io/sv29c/?view_only=ab88f291fc714327b07388faaf41e964 .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEvaluation of the Election\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter consenting to the survey, participants were asked to think back to when they first learned about the results of the second round of the 2023 Presidential elections. Gender-matched pollsters wrote down their brief responses to ensure participants thought about the election night, which included the details about the circumstances in which they learned about the election results. After that, participants rated the vividness and valence of their recollection on a scale of 1 to 5, 1 being not vivid at all, and 5 being very vivid. They then answered agency-related questions for individual, (\u0026ldquo;\u003cem\u003eHow much do you think you as an individual and your actions shaped this event?\u003c/em\u003e\u0026rdquo;), political group (\u0026ldquo;\u003cem\u003eHow much do you think the political group you feel closest to shaped this event?\u003c/em\u003e\u0026rdquo;), and national agency (\u0026ldquo;\u003cem\u003eHow much do you think your nation shaped this event?\u003c/em\u003e\u0026rdquo;), again on a scale of 1 to 5, 1 being not at all, and 5 being a lot. To assess the impact of the election further, we asked how much they followed the news then, compared to pre-election, and how much they talked about the election results with their close circle. They then rated the personal, national, international and generational importance of the presidential elections.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePast and Future National Events\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the next section, we counterbalanced the design such that participants either first mentally traveled to the collective past and then made a future projection, or vice versa. For the collective past task, they were asked to think back to the last 25 years and remember a national event \u003cem\u003eas important as\u003c/em\u003e the 2024 election (\u0026ldquo;\u003cem\u003eCan you remember a collective event as important as the Presidential Elections of 2023 that happened in the past 25 years? What was that event\u003c/em\u003e?\u0026rdquo;) For the future task, they were asked to project the next 25 years and imagine an event that would be \u003cem\u003eas important as\u003c/em\u003e the 2024 election (\u0026ldquo;\u003cem\u003eCan you imagine a collective event as important as the Presidential Elections of 2023 that is likely to happen in the next 25 years? What is that event\u003c/em\u003e?\u0026rdquo;). For both past and future events, participants rated valence, vividness, agency (individual, political group, nation) and importance (individual, national, international, generational) just like their responses for presidential elections. They were also asked to rate how similar the past and the future event was to the presidential election, and remember/estimate when the event happened/will happen. There was no effect of counterbalancing on any of the future variables. This test offers no problem in the future analyses, as we did not use international importance in our analyses.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003e\u003cem\u003eScales\u003c/em\u003e\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eAfter the mental time travel section, Need for Closure (NFC), System Justification (SJ, Collective Angst (CA) and Collective Nostalgia (CN) were measured. We used a short 15-item Need for Cognitive Closure Scale, scaled from 1 to 6 (Webster \u0026amp; Kruglanski, 1994; Roets \u0026amp; Van Hiel, 2007, Turkish adaptation by Seker \u0026amp; Akman, 2015), which broadly measures the need for certainty (\u0026ldquo;I dislike questions which could be answered in many different ways\u0026rdquo;). This inventory was found to be highly reliable (36 items; \u0026alpha; = .72). In addition, participants filled out a 8-item System Justification Scale on a scale of 1 to 5 (Kay \u0026amp; Jost, 2005, Turkish adaptation by Yıldırım, 2010, \u0026alpha; = .67), which assessed their attitudes about the status quo (\u0026ldquo;In general, Turkey is just and fair.\u0026rdquo;). The Collective Angst and Nostalgia scales were adopted from Smeekes et al. (2018)\u0026rsquo;s study, and included four items each. The scales contained items such as \u0026ldquo;I am worried about the future vitality of Turkey\u0026rdquo; for CA and \u0026ldquo;I get nostalgic when I think back of Turkey in past times\u0026rdquo; for CN. These scales were followed by demographic questions, which captured ideological divides like religiosity, left/right divide, secularism, patriotism, previous and current voting behavior, party identification, age, gender, SES, education and city of origin. See supplementary information for the full questionnaire in English.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTo identify the collective MTT pathways linking the election night, collective memories and collective future projections, we first conducted a factor analysis on event ratings for the\u003cem\u003e\u0026nbsp;election night\u003c/em\u003e and the \u003cem\u003ecollective past event\u003c/em\u003e. The characteristics of the factors, defined by the prominent event ratings, enabled us to identify the MTT pathways between the election night and the collective past event. We grouped each participant according to how well they fit into a particular factor (explained below), and checked if these pathways mapped onto the individual level sociopolitical differences. Lastly, using this event-based (election night and collective past) classification, we compared groups\u0026rsquo; future projections.\u003c/p\u003e\n\u003cp\u003eThere are several novelties in our approach. First, we used factor analysis to identify shared features across election and past event recollections. This allowed us to identify common characteristics between responses even though people may have identified separate events. In essence, we used factor analysis to reduce the individual level \u003cem\u003eevent ratings\u003c/em\u003e into meaningful clusters of \u003cem\u003emental time travel pathways\u003c/em\u003e. This aligns with typical uses of factor analysis for data reduction (Russel, 2002). Second, we utilized pathways derived from event ratings and compared how individuals in different pathways projected the future, focusing on event characteristics that mapped onto individual differences in sociopolitical characteristics and demographics. In other words, unlike many studies looking at political contexts, we did not group participants based on demographics or sociopolitical identity, but rather on how people recalled election night and collective past.\u003c/p\u003e\n\u003cp\u003eWe present our findings under three sections: \u003cem\u003edefining\u0026nbsp;\u003c/em\u003ethe pathways through factor analysis, \u003cem\u003eunderstanding\u0026nbsp;\u003c/em\u003ethe pathways through sociopolitical characteristics, and \u003cem\u003eutilizing\u0026nbsp;\u003c/em\u003ethe pathways in understanding different collective future imaginations.\u003c/p\u003e\n\u003ch2\u003eDefining Pathways: from Election Night to the Collective Past\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe conducted an exploratory factor analysis on ratings for the election night and the past event memories, using SPSS (version 30). Specifically, we included agency (individual, political group, nation), importance (individual, national, international, generational), valence and vividness ratings of both the election night and the past event, as well as how much participants followed the news right after the election, how much they talked to their close circle after the election, and the similarity between the election night and the subjective temporal distance between the election night and the past event in the analyses. After preliminary analyses, vividness of the past event and following the news after the election were dropped from the analysis as their communality scores were below .25 (Appendix A).\u003c/p\u003e\n\u003cp\u003eWe explain each one of the four factors in terms of prominent event ratings that characterize them below. We then identify a single best-fit factor for each participant, and describe the sociopolitical differences across the individuals whose mental time travel pathways are best represented by that particular factor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFactor 1: Election Reflection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe first factor was characterized by high scores for \u003cem\u003eelection night\u003c/em\u003e \u003cem\u003eimportance\u0026nbsp;\u003c/em\u003eon personal, generational and national levels, the \u003cem\u003evividness\u0026nbsp;\u003c/em\u003eof the election night, how much the participants \u003cem\u003etalked about the election night\u003c/em\u003e with their close circle, and the \u003cem\u003eagency of the Turkish nation\u0026nbsp;\u003c/em\u003eon the election night. Thus, the participants who are the best fit for this factor scored high on various measurements of importance of the election night, remembered it vividly, talked about the election night with their close circle, and believed that the Turkish nation had high agency on the election night. All points to reflecting on \u003cem\u003eelection night\u003c/em\u003e, so we will be referring to this factor as the \u003cem\u003eelection reflection\u0026nbsp;\u003c/em\u003epathway from now on.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFactor 2: Recent Past Importance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe second factor was characterized by high scores in \u003cem\u003eimportance of the past event\u0026nbsp;\u003c/em\u003eon national, generational and personal levels, and the \u003cem\u003etemporal distance\u003c/em\u003e between the election night and the past event. A negative correlation of temporal distance meant that a good fit for this factor was characterized by less temporal distance between the election night and the past event. Overall, participants who are a better fit for Factor 2 had high ratings on the importance of a past event that was closer to the present. Thus, this factor will be referred to as the \u003cem\u003eRecent Past Importance\u003c/em\u003e pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFactor 3: Agentic Past Achievement\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe third factor was characterized by \u003cem\u003epast agency\u003c/em\u003e, specifically past agency of the political group, individual, Turkish nation, and \u003cem\u003evalence of the past event\u003c/em\u003e. Overall, this suggests that Factor 3 was characterized by positive past events that had high agency on individual, national, and political group level. Thus, this group will be referred to as \u003cem\u003eAgentic Past Achievement\u0026nbsp;\u003c/em\u003epathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFactor 4: Election Glorification\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe fourth factor was characterized by the \u003cem\u003evalence of the election night\u003c/em\u003e, \u003cem\u003eindividual and political group agency\u003c/em\u003e at the election night as well as similarity between the election night and the past event. Thus, Factor 4 is characterized by a positive election night recollection with high individual and political group agency. The similarity variable had a negative loading, meaning, the past event differed from the election night in terms of similarity. This might be an optimistic way of distancing from a suboptimal past through a general election win. This factor will be referred to as the \u003cem\u003eElection Glorification\u003c/em\u003e pathway.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003cem\u003ePattern Matrix with Principal Axis Factoring\u003c/em\u003e\u003c/h4\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eElection Reflection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eRecent Past Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eAgentic Past Achievement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eElection Glorification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Generational Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Personal Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, National Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, International Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Vividness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Turkish Nation Agency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003ePast Event, National Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003ePast Event, Generational Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003ePast Event, Personal Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eDistance between Election and Past Event\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e-.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003ePast Event, Political Group Agency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003ePast Event, Individual Agency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003ePast Event, Valence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003ePast, Turkish Nation Agency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Valence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Individual Agency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eElection Night, Political Group Agency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eSimilarity between Election and Past Event\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eUnderstanding the Pathways: Sociopolitical Characteristics\u003c/h2\u003e\n\u003cp\u003eThe factor scores were calculated by the regression method, which predicted the location of each individual on the factor with respect to standardized observed values of the items with a mean of 0 (DiStefano, Zhu, M\u0026icirc;ndrilă, 2009). This led to 4 standardized factor scores for each participant, negative and positive. The highest factor coefficient was chosen for each participant, as the higher the coefficient, the higher the participant scored in the variables that contributed to that factor. However, there were some participants whose highest factor score was negative, suggesting they had negative correlations, and were not a good fit to any of the factors. They were excluded from the analyses (N = 23). Thus, the chosen factor could be described as the factor that is the best fit for the participant. In the end, Election Reflection factor had 71 participants (39 Female, 32 Male), Recent Past Importance factor had 105 participants (58 Female, 47 Male), Agentic Past Achievement factor had 86 participants (35 Female, 51 Male), and Election Glorification factor had 118 participants (51 Female, 67 Male). See Appendix B.\u003c/p\u003e\n\u003cp\u003eBefore explaining characteristics of participants in pathways, it\u0026rsquo;s imperative to highlight that these factors are derived from event characteristics like vividness, valence, importance ratings and agency scores for both election night and the past event. We did not include any demographic variables at any point, so the differences we find points to a successful parsing out via event characteristics that captured socio-political differences in collective MTT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVoting Behavior of Across Pathways\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs Table 2 conveys, pathways diverge in terms of voting behavior. Election Reflection and Recent Past Importance pathways mostly included opposition participants, Election Reflection more so than Recent Past Importance. The Agentic Past Achievement pathway is more balanced, as the participants who are in this MTT pathway are divided between the two candidates\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e6\u003c/sup\u003e. The Election Glorification pathway, on the other hand, overwhelmingly consisted of Erdogan supporters. We argue these distinctions offer an insight beyond binary winner/loser distinctions after an election. The proper \u0026ldquo;winners\u0026rdquo; are the election glorifiers, who open an optimistic page via the election with individual and political group agency on election night. The \u0026ldquo;losers\u0026rdquo; are participants in the Election Reflection and Recent Past Importance pathways. However, they diverge in the way they mentally travel from the election night to the past: the participants in the election reflection pathway are still processing and reflecting on the \u003cem\u003eelection\u003c/em\u003e, vividly remembering and talking about it with their close circle, all the while highlighting the agency of the nation and importance of the election night. The Recent Past Importance participants simply give an event from the recent past. The Agentic Past Achievement pathway, on the other hand, provides a heterogenous point of comparison where opposition and Erdogan voters converge: through a positive past high in individual, political group, and national agency.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eVoting Behavior across Pathways\u003c/em\u003e\u003c/h4\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"471\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathway\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVote in Round 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCounts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of Dimension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eElection Reflection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eKilicdaroglu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e84.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eErdogan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e11.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eRecent Past Importance\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eKilicdaroglu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eErdogan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e20.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e12.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eAgentic Past Achievement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eKilicdaroglu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e39.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eErdogan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e48.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e11.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eElection Glorification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eKilicdaroglu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eErdogan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e91.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSee Table 3 for how demographic, sociopolitical and psychological measures (system justification, collective nostalgia, collective angst) vary across MTT pathways. To this end, we conducted one way ANOVAs with each of the variables as the dependent variable, and the best fit pathway as independent variable. We provide a summary table highlighting differences between pathways, and present the full set of statistical results in Appendix C.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eCharacteristics of Pathways. Pathways go from opposition heavy to pro-Erdogan from left to right. Mean is reported in parentheses.\u003c/em\u003e\u003c/h4\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElection Reflection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecent Past Importance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgentic Past Achievement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElection Glorification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e- (\u003cem\u003e37.7\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eYounger (\u003cem\u003e36.2\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eOlder (\u003cem\u003e41.5\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eOlder (\u003cem\u003e42.6\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParty Identification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMore (\u003cem\u003e4.14\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eLess (\u003cem\u003e3.68\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e- (\u003cem\u003e4.0\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e- (\u003cem\u003e4.04\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeft/right\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eLeft (\u003cem\u003e1.94\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eLeft (\u003cem\u003e2.07\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eRight (\u003cem\u003e3.16\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eMost Right (\u003cem\u003e4.32\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligious/secular\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eLeast (\u003cem\u003e2.15\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eLeast (\u003cem\u003e1.21\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eLess (\u003cem\u003e2.56\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eMost (\u003cem\u003e3.09\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmotional Response\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMore (\u003cem\u003e2.85\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eLess (\u003cem\u003e2.79\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e- (\u003cem\u003e2.44\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e- (\u003cem\u003e1.91\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEconomic Impact\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eWorst (\u003cem\u003e-1.55\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eWorse (\u003cem\u003e-.44\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eWorse (\u003cem\u003e-.29\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eBest (.\u003cem\u003e46\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystem Justification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eLess (\u003cem\u003e2.26\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMore (\u003cem\u003e2.47\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eMore (\u003cem\u003e2.88\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eMost (\u003cem\u003e3.28\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollective Anxiety\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMost (\u003cem\u003e4.43\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMost (\u003cem\u003e4.30\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eMore (\u003cem\u003e3.58\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eLeast (\u003cem\u003e3.0\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollective Nostalgia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMost (\u003cem\u003e4.16\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMore (\u003cem\u003e3.80\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eMore (\u003cem\u003e3.59\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eLeast (\u003cem\u003e3.11\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e Due to a large number of pairwise comparisons, we denoted the hierarchy among the pathways as Most, More, Less, Least. The sign \u0026ldquo;-\u0026rdquo; means that there is no significant pairwise comparison with that pathway. The average scores are reported in parentheses. Except for economic impact rated between -2 to +2, all other ratings were from 1 to 5. All pairwise comparisons are corrected for multiple comparisons.\u003c/p\u003e\n\u003cp\u003ePathways divide on the left-right axis: Election Reflection and Recent Past Importance pathways are significantly more left wing, while Agentic Past Achievement and election glorifying pathways are more right wing. Agentic Past Achievement and Election Glorification pathways further differentiate in terms of religion and future economic expectation: election glorifiers are more religious and optimistic than participants in Agentic Past Achievement pathway. Even though Election Reflection and Recent Past Importance participants are both left-wing, less religious and opposition heavy, they differed in party identification \u0026nbsp;and emotional response to election. Specifically, participants in Recent Past Importance pathway identify with their party less and report being less emotionally affected than participants in the Election Reflection group.\u003c/p\u003e\n\u003ch2\u003eUtilizing the Pathways: Differences in Future Event Characteristics\u003c/h2\u003e\n\u003cp\u003eUpon defining and understanding the pathways derived from event ratings of the election and an equally important collective past event, we now report findings on future projections across pathways.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFuture Event Valence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFuture event valence differed across pathways, Welch\u0026rsquo;s \u003cem\u003eF\u003c/em\u003e(3, 194.61) = 10.84, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, partial \u0026eta;\u003csup\u003e2\u003c/sup\u003e = .08. All post hoc comparisons were significant with the negativity of the future events increasing from Election Glorifying (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= -.24, CI [-.53, .05]), Agentic Past (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= -.15, CI [-.49, .19]), Recent Past Importance (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= -1.18, CI [-1.49, -.87]) and Election Reflection (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= -1.01, CI [-1.39, -.64]), post hoc tests: \u003cem\u003et\u003c/em\u003e(159.65) = -3.21, \u003cem\u003ep\u003c/em\u003e = .009, \u003cem\u003ed\u003c/em\u003e = .48, \u003cem\u003et\u003c/em\u003e(154.15) = -3.29, \u003cem\u003ep\u003c/em\u003e = .007, \u003cem\u003ed\u003c/em\u003e = .54, \u003cem\u003et\u003c/em\u003e(160.81) = -4.45, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = .64, \u0026nbsp;\u003cem\u003et\u003c/em\u003e(219.06) = -4.54, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = .59. Not surprisingly, losing the election led to a more negative future for those on the losing side, except for the losers in the agentic past achievement pathway. However, the outlook was negative overall.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003e\u003cem\u003eFuture Event Agency\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eHow did MTT pathways differ in future agency? To understand this, we conducted a 3X4 repeated measures ANOVA, where the agency rating of the event (individual, national, political group) was the within subjects variable, and the MTT pathway was the between subjects variable. There was a main effect of agency, \u003cem\u003eF\u003c/em\u003e(2, 752) = 201.6, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, partial \u0026eta;\u003csup\u003e2\u003c/sup\u003e = .35, where across all pathways, national agency was the highest (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 3.47, CI [3.32, 3.61]), followed by political group (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 2.92, CI [2.76, 3.08]), and individual (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 1.98, CI [1.83, 2.12]) agency.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMore importantly, this agency pattern differed across MTT pathways, \u003cem\u003eF\u003c/em\u003e(6, 752) = 7.42, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, partial \u0026eta;\u003csup\u003e2\u003c/sup\u003e = .06. (Figure 4). The \u003cem\u003ehigher national agency over political group agency\u003c/em\u003e pattern disappeared for opposition pathways. For the Election Reflection and Recent Past Importance pathways, future national agency (Election Reflection: \u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 3.28, CI [2.96, 3.61], Recent Past Importance: \u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 3.57, CI [3.30, 3.84]) was higher than future political group agency (Election Reflection: \u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 2.49, CI [2.13, 2.86], Recent Past Importance: \u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 2.47, CI [2.17, 2.77]), \u003cem\u003et\u003c/em\u003e(376) = 4.66, \u003cem\u003eptukey\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = .54, \u003cem\u003et\u003c/em\u003e(376) = 7.94, \u003cem\u003eptukey\u003c/em\u003e \u0026lt; .001, \u003cem\u003ed\u003c/em\u003e = .68. There were no differences for Agentic Past Achievement and Election Glorification pathways. This can be understood as the effect of winning (vs. losing) an election. While losing an election is detrimental to the political group agency, winning leads to a political group agency that is on par with national agency. This is understandable, as winning an election gives a political party the power to determine the nation\u0026rsquo;s future for a limited time. However, despite almost 50% voting for the losing candidate, participants in the Agentic Past Achievement pathway maintained a high political group agency on par with those in the Election Glorification pathway.\u003c/p\u003e\n\u003cp\u003eOne might argue that this higher political group agency was a virtue of combining both the winners and the losers in the Agentic Past Achievement pathway, as political group agency in this pathway differed as a factor of voting behavior, \u003cem\u003et\u003c/em\u003e(74) = 2.18, \u003cem\u003ep\u003c/em\u003e = .03, \u003cem\u003ed\u003c/em\u003e = .50. Winners in the Agentic Past Achievement pathway indeed had higher political group agency (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 3.88, CI [4.33, 3.43]) than losers in the same pathway (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 3.12, CI [3.68, 2.56]). However, the political and the national agency of the losers in the agentic past achievement pathway did not differ, \u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 3.44, CI [2.91, 3.97]), \u003cem\u003et\u003c/em\u003e(33) = 1.82, \u003cem\u003ep\u003c/em\u003e = .08. Thus, the pattern of future political agency not suffering for the Agentic Past Achievement factor held true across voting behavior. Further, the future political agency of the losers in the Agentic Past Achievement pathway was still higher than the future political agency of opposition heavy Election Reflection (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 2.49, CI [2.13, 2.86]) and Recent Past Importance (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 2.47, CI [2.17, 2.77]) pathways. This is further proof that we are capturing a distinct mental time travel pathway than what would have been captured by simple voting behavior.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhat might be the reason for the resilience of the agentic past achievement pathway? Note that they were remembering a positive past event that the nation, as well as their political group had high agency over. This stop at an agentic, positive collective past seems to be driving a more positive (described in the previous section) and agentic future.\u003c/p\u003e\n\u003cp\u003eAlthough we focus on mental time travel and its effects on a collective level, \u003cem\u003eindividual future agency\u003c/em\u003e is important in the way people engage with the collective. It is also important in how individuals cope after the elections are over and go on to their daily routine. We observed a divergence in the future individual agency of the two opposition heavy pathways: \u003cem\u003eRecent Past Importance\u0026nbsp;\u003c/em\u003e(\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 1.53, CI [1.26, 1.80]) scored lower than Agentic Past Achievement (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 2.24, CI [1.95, 2.56]) and Election Glorification (\u003cem\u003eM\u0026nbsp;\u003c/em\u003e= 2.35, CI [2.09, 2.60]), \u003cem\u003et\u003c/em\u003e(376) = 3.47, \u003cem\u003eptukey\u003c/em\u003e = .03, \u003cem\u003ed\u003c/em\u003e = .51, \u003cem\u003et\u003c/em\u003e(376) = 4.31, \u003cem\u003eptukey\u003c/em\u003e = .001, \u003cem\u003ed\u003c/em\u003e = .58. However, the future individual agency of the other opposition-heavy pathway, \u003cem\u003eElection Reflection\u0026nbsp;\u003c/em\u003epathway, was on par with mixed Agentic Past Achievement and pro-Erdogan Election Glorifiers. Considering the Recent Past Importance pathway had lower party identification and less emotional response to the election than the Election Processors, we speculate that party identification is preventing resignation, and offering a buffer against a steep loss of future individual agency even in the face of a political defeat.\u003c/p\u003e\n\u003cp\u003eHere, we observe two possible mitigation strategies upon losing an election: First, remembering a positive, agentic (national and political group) past protects \u003cem\u003efuture political group agency\u003c/em\u003e. Second, party identification buffers the loss of \u003cem\u003efuture individual agency\u003c/em\u003e. We argue that we can observe two \u003cem\u003epathway specific\u003c/em\u003e future agency buffers in the face of a substantial defeat: remembering a past where the political group, and the nation as a whole had agency (for future political agency) and party identification (for future individual agency).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, using an event-ratings-based categorization, we identified four divergent collective mental pathways. Our approach \u0026nbsp;highlights that memories of the past cued by a consequential election help retrieve equally vivid and important collective future projections (Appendix D) that vary in valence and agency. We demonstrated that the collective MTT pathways captured nuance beyond winner and loser voter groups, accounting for demographic (age, left-right, religiosity, party identification), motivational and emotional (system justification, collective nostalgia, collective angst) differences. Our approach is unique in how it uses a widely experienced political event (presidential elections) as a collective temporal anchor to reveal insights into collective MTT and sociopolitical leanings. Our findings go beyond illustrating thematic overlap between collective past and future to capture variations in sociopolitical identities and future simulations.\u003c/p\u003e\n\u003cp\u003eSpecifically, our data shows the complex interaction between various aspects of what is collectively remembered and the kind of future it evokes. First, high party identification buffered the loss of future individual agency, despite not providing a rosier future. The literature on election stress and wellbeing highlights \u0026ldquo;anticipatory coping\u0026rdquo;, which is preparing for an event before it occurs, increasing feelings of control and wellbeing. MTT into the future, then, emerges as a way to cope with post-election dip in psychological wellbeing. Thus, we propose that reflecting on the election upon losing, characterized by talking to close others about it, acknowledging its importance and accepting it as the will of the nation is a way of healthy coping. It leads to a negative future, but one with higher individual agency. The key for this pathway seems to be party identification. In the end, psychological wellbeing at the individual level is connected to party identification on the social level.\u003c/p\u003e\n\u003cp\u003eSecond, we found that some members of a nation come together in how they remember the past and project a future. They remember a positive agentic past where both their political group and nation had an effect, and in turn they projected a rosier and more agentic future- both in terms of political group and national agency. In his attempt to understand what transforms a body of people into a nation, Anderson (1983) coined the term \u0026ldquo;imagined communities\u0026rdquo;. Defining a nation as a social construct rather than a natural entity, he argues that because one can not simply \u003cem\u003eknow\u003c/em\u003e all of the members of their nation, one fills in the gap with their imagination. Taking Anderson\u0026rsquo;s definition of a constructed nation, we argue that we are capturing an imagination as a nation in this pathway. This has reflections in collective memory literature, in schematic narrative templates of a nation (Wertsch, 2021) that ascend generations and shapes collective thinking (e.g. US as the city on a hill), and in the Turkish case, stable dimensions of collective memory even after a coup attempt (Mutlut\u0026uuml;rk et al., 2022).\u003c/p\u003e\n\u003cp\u003eWe argue that this methodology of focusing on event based mental time travel pathways as opposed to voting behavior can help understand the nation as a whole, but heterogeneous entity. While we acknowledge that our sample does not have perfect representation, our approach allows us to achieve nuance nevertheless. One possible future venue of utilizing this methodology would ask if evoking a particular collective memory can manipulate the particular mental time travel pathway an individual takes \u0026ldquo;naturally\u0026rdquo;. Probing if we can switch the natural pathways found in this representative and ecologically valid data would be crucial for various interventions. Extant literature suggests that this manipulation works with valence (Ionescu et al, 2024), and future work might tackle switching pathways after an electoral defeat.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, although our results take a snapshot after a consequential election, future work needs to tackle the dynamic nature of collective representations, and identify if mental time travel pathways derived after various consequential events reflect a similar pattern. Validating this methodology across different cultures and political contexts is crucial. We know that people in Western societies usually exhibit a positivity bias for the personal past and a negativity bias for the collective past (Shrikanth \u0026amp; Szpunar, 2021), as well as for personal and collective future (Mert \u0026amp; Wang, 2024; Shrikanth et al., 2018; Yamashiro \u0026amp; Roediger, 2019). Chinese people, on the other hand, do not (Deng et al., 2023; Mert et al., 2023; see Wang \u0026amp; Mert, 2025 for a review). Testing mental time travel pathways across non-Turkish samples might unearth how subgroups within a nation create different imaginations, which would help build efficient communication strategies to combat possible downfalls arising from this divergence.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAltunkaya, T. (2023, April 19). 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Valence-based biases in collective temporal thought: The role of question framing, culture, and age. Memory \u0026amp; Cognition, 1-16.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bbc.com/news/world-us-canada-56004916\u003c/span\u003e\u003cspan address=\"https://www.bbc.com/news/world-us-canada-56004916\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://en.wikipedia.org/wiki/2022%E2%80%932023_Brazilian_election_protests\u003c/span\u003e\u003cspan address=\"https://en.wikipedia.org/wiki/2022%E2%80%932023_Brazilian_election_protests\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bbc.com/news/articles/cwy5ypkn7kjo\u003c/span\u003e\u003cspan address=\"https://www.bbc.com/news/articles/cwy5ypkn7kjo\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bbc.com/news/world-europe-65743031\u003c/span\u003e\u003cspan address=\"https://www.bbc.com/news/world-europe-65743031\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Turkish Institute of Statistics report has 7.5% without formal education, 22.7% primary school graduates, 22.7 middle school graduates, 23.2% high school graduates, and 23.9% with university or higher education degree (TUIK, 2023)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The mixed voting behavior in the Agentic Past Achievement is curious due to 20\u0026thinsp;+\u0026thinsp;years of polarization. To this end, we looked if the participants in this pathway ever voted for Erdogan. The results were a clean 50/50, where 50% of them previously voted for Erdogan at least once.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e All of the post-hoc tests reported are Games-Howell tests, unless it is reported as Tukey\u0026rsquo;s.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Koç University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"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":"collective mental time travel, collective memory, future projection, election memory","lastPublishedDoi":"10.21203/rs.3.rs-6789456/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6789456/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eResearch on collective mental time travel has shown thematic links between past and future events, but how specific events cue past and future events in relation to sociopolitical identity remains underexplored. Connecting the collective past to the future, we primarily focused on event characteristics to identify collective mental pathways using a data-driven, bottom-up approach. We focused on the 2023 Turkish Presidential Election as a pivotal event anchoring collective memories and related future projections. Using representative in-person interviews, we asked participants to evaluate the election, recall related past and future collective events, and rate each event\u0026rsquo;s characteristics (e.g. Valence, Vividness, Agency, Importance). Our analyses identified four unique pathways of traveling to the collective past from the election night based on these ratings. The resultant pathways mapped onto sociopolitical divides in age, voting behavior, party identification, religiosity and political orientation. These pathways revealed how certain ways of thinking of the past and the future offer psychological buffers against electoral loss. Specifically, processing the election protected future \u003cem\u003eindividual\u003c/em\u003e agency, and remembering an agentic, inclusive past scaffolded future \u003cem\u003epolitical group\u003c/em\u003e agency. Our findings point to shared cognitive processes behind sociopolitical divides.\u003c/p\u003e","manuscriptTitle":"Beyond Winners and Losers: Collective Mental Time Travel Pathways Buffer Future Agency after Elections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-04 09:49:31","doi":"10.21203/rs.3.rs-6789456/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":"8805f71d-3647-49ff-804f-114e4f1bcb0a","owner":[],"postedDate":"June 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49321304,"name":"Psychology"}],"tags":[],"updatedAt":"2025-06-04T09:49:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-04 09:49:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6789456","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6789456","identity":"rs-6789456","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}