Historical Memory Law and Retoponimization Processes in Spain

Historical Memory Law and Retoponimization Processes in Spain | 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 Article Historical Memory Law and Retoponimization Processes in Spain Samuel Esteban Rodríguez, Zhaoyang Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8622574/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 In Spain, the state has frequently used street names symbolically: after the Civil War, names associated with the Second Republic, as well as some earlier ones, were re-moved and replaced with those from the so-called Nationalist (or rebel) side. Many of these were later removed after Franco’s death; however, some had persisted through-out the democratic period. In 2007, a controversial national Historical Memory Law was passed, mandating the removal of street names that glorify Francoism. The aim of this study is to assess the intensity with which this law has been implemented and to examine potential regional differences. To this end, street name changes across Spain related to the Franco regime between 2001 and 2021 were analyzed, using the Electoral Census Street Directory as the primary data source. The law has led to the widespread removal of names associated with Francoism; however, its impact has not been uni-form across the country, with the highest number of changes occurring in inland provinces. Humanities/History Social science/History Social science/Politics and international relations Historical Memory Law Spain street nomenclature toponymy toponymic change Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction In Spain, the publication in the Official State Gazette (BOE) of Law 20/2022, of 19 October, on Democratic Memory[ 1 ] marked a new phase in the legal treatment of collective memory regarding the Spanish Civil War and the subsequent dictatorship of Francisco Franco. Fifteen years had passed since the approval of Law 52/2007, of 26 December, better known as the Historical Memory Law (HML), which recognized and extended rights and established measures in favor of those who suffered persecution or violence during the Civil War and the dictatorship [ 2 ]. The repeal of this law with the entry into force of Law 20/2022 provides a timely opportunity to assess its implementation over the period since its enactment. Law 52/2007 established the obligation to remove from public spaces any symbols, plaques, or references that glorified the 1936 military uprising, the Civil War, or the subsequent Franco dictatorship (Article 15). As stated in its preamble, the law aimed to transform public space into a shared space of encounter and memory for citizens. To achieve this goal, public administrations were required to remove all personal and collective references that, in any way, amounted to an exaltation of the Franco regime (Article 15). Failure to comply could result in sanctions such as the withdrawal of public subsidies and grants—measures to which local authorities are particularly sensitive. There are strong connections between geographical space and memory [ 3 ]. Consequently, processes of toponymic change (re-toponymization) and interventions in the symbolic use of street names are not new in Spain. In other historical periods, street name changes have also occurred by legal mandate. One such process was initiated by Franco’s government during and after the Civil War, during which numerous references from the liberal period and nearly all from the Republican era were removed and replaced with names honoring values, events, and figures from the Francoist side [ 3 ][ 4 ]. In some municipalities, these names were changed at the beginning of the transition to democracy; however, in others, much of this nomenclature remained in place . The naming and labeling of streets fall under municipal authority [ 4 ]. Nevertheless, certain traditional limitations have applied to this municipal autonomy: for example, the use of names that glorify criminal acts such as terrorism is not permitted, nor are names that violate public principles or morality [ 4 ]. To these constraints were added those introduced by Law 52/2007, now incorporated into Article 35 of Law 20/2022, which, like its predecessor, applies uniformly across the entire national territory. Given the national scope of the HML, one might expect a homogeneous application across the country. However, in substance, there are varying degrees of sensitivity among the Spanish population—and among the political groups governing each administration. As was the case with Law 20/2022, the HML was not approved unanimously by the Cortes Generales (nor even by a broad majority) and was criticized for imposing a single version of history. Its implementation has also been controversial [ 4 ]. Therefore, given the distribution of competences over this matter, territorial differences in the law’s application and its impact on street nomenclature are likely. Since the HML lacks transitional provisions and does not provide a specific list of names to be removed, these differences may manifest in at least three ways: The timing of implementation, the number of streets with references to the Franco regime that were removed, and the specific individuals and events to which these references pertain. This study focuses on analyzing these three dimensions. Using the Street Directory of the Electoral Census (CCE) published by the National Institute of Statistics (INE) as the primary data source, we have examined changes in street names containing references that could be subject to removal under the HML. The study period spans from 2001 to 2021, and the analysis is conducted at the national, autonomous community, and provincial levels. The methodology section details the research procedures. The results section first presents the situation in 2001, followed by the evolution of aggregated data and a characterization of provinces according to the number of streets related to the Franco regime that were removed at different times. Finally, the frequency distribution of the affected references is analyzed. A discussion section follows the results, and the paper concludes with a summary of the main findings. 2. Materials and Methods The study of street names allows for the characterization of social space [ 5 ]. In relation to the subject of this study, it enables the identification and quantification of nomenclature associated with the Franco regime. The Street Directory of the Electoral Census (CCE) published by the National Institute of Statistics (INE) provides the names of all streets in Spain on a regular basis; since 2007, it has been semiannual. Before 2007, the periodicity was annual until 2004, and prior to 2004, only the street directory of July 2001 is available for free download. The CCE assigns a unique identifier to each street. In different publications, along with this identifier, the name of the street is included if it exists. Monitoring the names of each street allows identifying which ones have changed. This has been done for all streets in Spain across all directories published between July 2001 and July 2021 [ 6 ]. 2.1 Identification of Name Changes Linked to Law 52/2007 Not all changes in street names are significant, nor can they all be linked to the Historical Memory Law (HML). Frequently, modifications relate to minor variations in the spelling of names; for example, those resulting from the use or omission of abbreviations. Additionally, parallel to the implementation of Law 52/2007, other processes of re-toponymization occur in Spain. Notably, these include those related to the country's multilingual reality [ 4 ]; that is, the translation of names into various regional languages. In such cases,the changes are primarily linguistic rather than ideological. For instance, a street named "Calle de José Antonio" might be translated to "Carrer de Josep Antoni" in Catalan regions without altering its reference to a figure associated with the Franco regime. Therefore, distinguishing changes driven by the HML from those arising from linguistic adaptation or other local initiatives requires careful analysis. To focus the study on name changes related to Law 52/2007, streets with names potentially subject to the application of its Article 15 were first identified. As previously noted, Law 52/2007 does not include an annex listing names to be removed, nor has it been developed through regulatory provisions. In reality, there is no official and exhaustive list of names to be removed. Therefore, the names potentially subject to this law have been drawn from lists published in various studies on the topic. These include those by[ 5 ][ 7 ], the proposal report by the Madrid City Council's Historical Memory Commissioner on street name review [ 8 ], the database from Deberiadesaparecer.com (2020), the report on Francoist symbols in Carmona, Seville[ 9 ], the list of towns in the province of Ávila with Francoist-related nomenclature published by Foro por la Memoria (n.d.), and the lists of officers from Franco’s army published on Combatientes.es (n.d.). Additionally, the most frequent names appearing in streets that have undergone renaming were reviewed, and a list was constructed of those identified as linked to the Franco regime. These name sources were consolidated into a single list to eliminate duplicates. This unified list was then used to identify the presence of references related to Francoism in street names. Subsequently, their evolution was analyzed by examining the degree of similarity between the names of the same street in two consecutive street registries. Data on streets with references to the Franco regime were aggregated at the provincial, regional, and national levels, along with the total number of streets for each date. This information was used to group provinces according to their trends, derive statistics, and produce cartographic representations. The following steps were followed. Street registries from the 34 different dates previously specified were processed. The average number of streets per registry is 847,964; in total, 28,830,791 street names were analyzed. Tracking the name of each street was carried out using similarity measures, applying a comparison methodology based on trigrams. This technique, frequently used in natural language processing [ 10 ], involves decomposing names into recursive combinations of three characters, or trigrams. A string similarity index aligned with those implemented by Bird et al. (2009)[ 10 ] was used. The index (S) is calculated as the product of two ratios [ 1 ]: when comparing street names at two different points in time, the first ratio is the number of common trigrams (C) divided by the number of trigrams in the name at time 1 (T1); the second ratio is the number of common trigrams divided by the number of trigrams in the name at time 2 (T2). In this index, a value of 1 indicates complete similarity, while a value of 0 indicates no similarity, which occurs when both strings share no trigrams. Based on this similarity index, a complementary distance index (D) was derived; this is understood as the amount needed to reach the maximum similarity value, i.e., D = 1 – S [ 2 ]. Subsequently, their evolution was studied by examining the degree of similarity between the names of the same street in two consecutive street registries. Data on streets with references to the Franco regime were aggregated at the provincial, regional, and national levels, along with the total number of streets for each date. This information was used to group provinces according to their trends, and to derive statistics and cartographic representations. The following steps were then carried out. The street registries from the 34 different dates previously specified were processed. The average number of streets per registry is 847,964; in total, 28,830,791 street names were analyzed. The tracking of each street's name was performed using similarity measures, applying a comparison methodology based on trigrams. This technique, commonly used in natural language processing [ 10 ], involves decomposing names into recursive three-character combinations, or trigrams. A string similarity index consistent with those implemented by Bird et al. (2009) [ 10 ] was used. The index (S) is calculated as the product of two ratios [ 1 ]: when comparing street names at two different points in time, the first ratio is the number of common trigrams (C) divided by the number of trigrams in the name at time 1 (T1); the second ratio is the number of common trigrams divided by the number of trigrams in the name at time 2 (T2). In this index, a value of 1 indicates complete similarity, while a value of 0 indicates no similarity, which occurs when both strings share no trigrams. Based on this similarity index, a complementary name distance index (D) was derived; this is understood as the amount that must be subtracted from the similarity index to reach its maximum value. \(\:S=\frac{C}{{T}_{1}}\:·\:\frac{C}{{T}_{2}}\:\) [1] D = 1 - S [ 2 ] To detect street name changes, the denomination of each street in a given census edition was compared with its name in the subsequent edition. This comparison was performed using a string distance index. Prior to calculation, text strings were cleaned by removing special characters such as diacritical marks and punctuation. Streets whose names exhibit a distance greater than zero correspond to those that have undergone some form of change. However, many of these changes are minor. To focus the study on significant changes, a minimum distance threshold of 0.2 was established. Using 2001 as the reference year and applying a similarity index (S), streets showing any resemblance to names from the list of terms associated with Francoism were identified. These names were then aggregated and reviewed to exclude entries that could introduce ambiguity when detecting associations. After this refinement, streets were considered as bearing names potentially subject to the Historical Memory Law if they exhibited a similarity index greater than 0.8 with any name on the reference list. A mention was considered removed when a street’s name underwent significant changes or when the street was officially decommissioned. Regarding the latter, a street was deemed decommissioned if its unique identifier ceased to appear in subsequent censuses. Removed mentions were assigned to the intercensal period preceding the one in which the change was detected. 2.2 Data Analysis Streets containing references to the Franco regime in 2001, along with their changes in each successive directory, were aggregated at the provincial, autonomous community, and national levels, computed annually. The same aggregation was applied to the total number of streets in each census and to the number of distinct streets derived from merging all editions. With respect to 2001, the percentage of streets referencing Francoism relative to the total number of streets that year was calculated. In subsequent years, we counted the number of Francoist references from 2001 that had been replaced. This information was used to construct a time series tracking the behavior of each territorial unit over time, enabling the identification of growth patterns and the clustering of provinces with similar trajectories. Provinces were grouped into four clusters using clustering algorithms implemented by Tavenard et al. (2021) [ 11 ] in the tslearn library. Clustering was performed using cumulative values. Similarity between time series was measured using Dynamic Time Warping (DTW), a time-series alignment algorithm particularly suited for sequences with temporal shifts. The clustering results were mapped to analyze their geographical distribution, supplemented by data on the timing of changes in each unit and the number of streets replaced. The actual names of removed references were subjected to a frequency analysis at both national and cluster levels. To perform this, replaced street names were grouped by comparing all string pairs using the similarity index. The goal of this grouping was to determine how many streets referred to each individual figure or historical event. To minimize double-counting, replaced names appearing in the lists were considered linked to the same entity if their pairwise similarity index was equal to or greater than 0.5. The resulting groups were manually reviewed, and references to the same person not captured by the initial filter were re-grouped accordingly. For example, in the case of Franco, references included his full name, surname, military rank, honorific titles such as caudillo and generalissimo, as well as common variants. After grouping, the frequency of each reference was analyzed. Additionally, to provide a synthetic visual overview, a word cloud of the most frequently removed street names was generated using tools developed by[ 12 ]. 3. Results Using the methodology described, it is estimated that in the year 2001, across Spain as a whole, the number of streets subject to toponymic change under Article 15 of Law 52/2007—i.e., streets with names associated with the Franco regime—was 10,147. This represented approximately 1.33% of all streets nationwide. Regions with the lowest proportions were the Basque Country, Catalonia, and the Balearic Islands; at the opposite end of the spectrum were Castilla-La Mancha, Extremadura, and Castile and León (Fig. 1 ). Figure 2 presents the same variable in cartographic format, but at the provincial scale. There is a high concentration of streets whose names should change in all the provinces of the interior of Spain, both in both plateaus and in the Ebro Valley, with the only exception of Huesca. Its presence is also high in the Canary Islands, Cantabria and Murcia, as well as in some provinces of other coastal regions [ 13 ]. In the rest of the territory the proportion of streets linked to the Franco regime was smaller, especially in the Catalan and Basque provinces. 3.1. The process of re-ponymization in application of the Law of Historical Memory The number of streets repurposed in relation to the LMH between 2001 and 2021 has been 4931. The modification of the street gazetteer has taken place throughout the period considered, although, in Spain as a whole, there are two stages in which the number of changes is particularly high: the first occurs immediately after the approval of the regulation, in 2008; the second, which is when the most changes take place, around 2017 (Fig. 3 ). Between the two, there is a stage in which the rate of retoponymization decreases; In the last years of the series, the number of name changes also decreases. At the level of the Autonomous Communities (Fig. 4 ), the changes are of lesser volume in those that had a lower presence of names susceptible to re-on-ponymization in 2001. In this regard, both Catalonia and the Basque Country are paradigmatic cases, although the evolution is also similar in other regions such as Andalusia. At the other extreme, in that of the regions with the most changes, the 3 communities that in 2001 had a higher proportion of names related to the Franco era stand out. At the scale of the provinces, the high proportion of changes that have occurred in the inland areas bordering Portugal is striking, with the axis formed by Zamora, Salamanca and Cáceres clearly standing out (Fig. 5 ). These provinces, in line with what was observed at the regional level, had a high proportion of names related to the Franco regime in 2001. This direct relationship between the number of streets with mentions of Francoism and the number of streets re-established is the general pattern in the period that has been analysed. Despite this, there are some provinces that have particularities. We can mention the case of Asturias, where the concentration of streets related to the Franco regime was low in 2001 and, however, the proportion of changes between 2001 and 2021 is high. For their part, in the autonomous cities, the proportion of streets repurposed has been high in Melilla. 3.2. Groups of provinces based on detected name changes Based on the time series of the cumulative number of streets repurposed in application of Law 52/2007, the following 4 groups of provinces can be defined (Fig. 6 ). The first group corresponds to provinces in which the cumulative number of changes has been very high. Salamanca, Cáceres and Toledo are located there. Unlike what has been observed in Spain as a whole, since the approval of the law, this group has 3 moments in which, as can be seen in Fig. 7 , the changes are numerous. These occur around the years 2009, 2015 and 2018. The second group is mainly made up of provinces in the interior with a high concentration of names in 2001; by way of example, it is worth mentioning cases such as Madrid, Valladolid or Zaragoza. In these provinces, the process of re-ponymization has been intense, although of lesser importance than in the previous group. Despite this, it is a larger group of provinces and, in aggregate terms, has a greater number of streets revisited (Table 1 ). Its evolution presents cycles of retoponimization similar to those observed in Spain as a whole. Table 1 Number of provinces and number of streets renamed by groups Province groups Number of provinces Number of streets repurposed Changes in total (%) 1 3 1168 23,69 2 8 1466 29,73 3 18 1654 33,54 4 21 643 13,04 Total 50 4931 100,00 The third group is the one with the largest number of streets with mentions of the Franco regime re-ponymized, although the average per territorial unit is lower than in the previous ones. It is made up of 18 provinces from different regions; for example, Cantabria, León, Burgos, Navarra, Teruel, Valencia or Seville. Although the evolution of the group presents similar stages to those of the country as a whole, the proportion of streets re-ponymized in each phase presents singularities. In this group, in the years immediately following the implementation of the law of historical memory, the proportion of streets repurposed was very high. In addition, it has a less accentuated but longer second growth phase. 4) The fourth and last group is the one with the largest number of provinces. However, it has had fewer changes than the others. It includes all the provinces of the Canary Islands, Galicia, the Basque Country and Catalonia, most of Andalusia and also the provinces of Asturias, Huesca, Soria and Castellón. In all of them, except for the Canary Islands and some Galician provinces, the concentration of streets with names referring to the Franco regime was low in 2001. Its evolution, in cumulative terms, presents a little steep slope. In this group, the evolution of the number of replacements is different from that of the previous ones, which concentrate most of the modifications in the second period of re-on-the-top. In the fourth group there are fewer changes and those that do occur have their maximum peak just after the approval of the law. 3.3. Replaced toponyms In application of the Law of Historical Memory, the names that have been replaced most frequently are those referring to Franco himself, which account for 17.73% of the total. Among the streets that have been renamed, those referring to José Antonio Primo de Rivera are also very numerous; This is approximately 14.79% of those that have been modified. These, plus those that allude to General Mola, Calvo Sotelo and Salas Pombo, account for more than 50% of the changes. In total, modifications have been detected referring to 674 events or characters. The 26 names that have been replaced most frequently account for approximately 80% of the changes. In all the groups of provinces, the two names that have withdrawn the most coincide with those of Spain as a whole (Table 2 ). However, in other cases, the relative frequency and order of occurrence vary in each area. It is worth highlighting the case of Salas Pombo, numerous in the provinces of group 1, but without significant equivalences in the rest; In this group, the changes recorded affect a smaller number of names than in the rest (Table 3 ). In contrast, the diversity of replaced names is much greater in the fourth group, despite having fewer changes. Table 2 Names most frequently replaced in application of Law 52/2007 Number Proportion in Spain (%) Groups of provinces 1 2 3 4 Francisco Franco 17,73 3,61 6,14 5,54 2,21 José Antonio 14,79 3,45 4,99 4,44 1,72 General Mola 11,28 3,29 3,55 3,39 0,91 Calvo Sotelo 8,89 2,25 3,16 2,27 1,10 Pombo Rooms 2,53 2,49 Source: Street Map of the Electoral Census. Own elaboration Table 3 Names and streets most frequently revisited in application of Law 52/2007 Groups (1) Names (2) Streets (3) Substitutions (4) Diversity (5) 1 86 1.168 13,58 7,36 2 157 1.466 9,34 10,71 3 273 1.654 6,06 16,51 4 158 643 4,07 24,57 Total 674 4.931 7,32 13,67 Source: (1) Groups of provinces. (2) Number of names replaced. (3) Number of streets retoponymized. (4) Average number of changes per name (5) Number of different names / Number of changes (%) Source: Street Map of the Electoral Census. Own elaboration In the replaced names, the mentions of the army are numerous. Due to their high frequency, those made to generals and senior commanders stand out (Fig. 8). In this group, in addition to those referring to Franco -who was a general-, there are many others. In addition to the mentions of the generalship, there are a high number of references to the rest of the officer corps, combatants of Franco's army and volunteers of the Blue Division. The names of battles and allusions to those who fell in combat are also frequent. In all cases there are names of specific people, places, dates and events. Although some references to individual soldiers appear on the streets that have been renamed, these are usually grouped under certain slogans; for example, Defensores de Oviedo. In any case, the references to the troops in the street are much less numerous than the references to the officers. Among the events are battles, such as the Ebro and the siege of the Alcázar of Toledo. In terms of dates, references to July 18, 1936 are the most numerous. In relation to casualties, the combatants who died and the people executed by militiamen on the Republican side are usually given generic names: the former fallen and the latter martyrs. In the replaced personal names, masculine names predominate; among women's pensions, that of Pilar Primo de Rivera has been the one that has been replaced on a greater number of occasions. In areas of social life other than military confrontation and politics, references to people from the world of culture have been eliminated, such as the painter Salvador Dalí, the writer Muñoz Seca or the composer Manuel de Falla; although, among these, as in the case of politicians active during democracy, the frequency of re-ponymization is low; approximately 2.55% compared to 48.72% for all names present in 2001. Although in the last street map that has been analysed there are some references to relevant figures of the Franco regime, their number is very small in relation to 2001. Most of the references to names present in the lists that survive correspond to characters from the world of culture. 4. Discussion In relation to the methodology used and in line with the work of Oto-Peralías (2017), it is worth noting the usefulness of the electoral census street map as a source of information on toponymy and, more specifically, its usefulness in identifying changes in it. The use of natural language processing techniques and similarity indices makes it possible to work with this data source, especially when the study area includes a large number of streets and the temporal scope is long, as is the case of this work. Despite this, the search for correspondences and variations presents some difficulties. One of the most problematic issues is the establishment of similarity and distance thresholds, as they are directly related to errors of omission and commission. As for the sources of names of people and events related to Francoism, the lists with the greatest scope that have been handled are the lists of army officers. Although attempts have been made to integrate different sources of information, these are not sufficiently exhaustive lists. It should be noted that, in the requests for the removal of streets submitted to the municipalities with which we have worked, relatively anonymous people appear with some frequency; The most typical cases are those of people who were members of a political party and town mayors whose mention some historical memory association requested to withdraw. In this work, there has not been an exhaustive list of public officials from the Franco era. Therefore, the total number of changes may vary in relation to that observed in the results. 5. Conclusions The results obtained reveal that the implementation of the Historical Memory Law (HML) has been intense. Approximately 5,000 streets in Spain have been renamed over a period of just 15 years as a direct consequence of the law. The HML has removed numerous references to the country’s history prior to the establishment of the current democratic system from public space. On many occasions, critics—particularly those who opposed the law’s approval—have argued that this process constitutes an attempt to rewrite history. However, as highlighted by García-Álvarez (2009) [ 3 ] and Izu-Belloso (2010) [ 4 ], many of these streets had previously been renamed during Franco’s dictatorship and in earlier political transitions. In this sense, it can be asserted that processes of re-toponymization have occurred frequently throughout Spain’s contemporary history. Regarding whether the application of the law has been homogeneous, the answer is clearly no. As demonstrated in the results, there are significant differences across regions, evident in all aspects analyzed: the number of streets renamed, the timing of implementation, and the names replaced. In terms of the number of renamed streets, the impact of the law has varied considerably across the territory. This variation largely depended on the number of streets bearing Francoist references at the time the law came into force. The most affected areas were the inland provinces of Spain, which preserved the highest number of such references. In contrast, regions such as Andalusia, the Basque Country, and Catalonia experienced a smaller impact. In these regions and in many cities, references to the main figures of Francoism were already removed at the beginning of the current democratic period[ 7 ]. With regard to the timing of implementation, significant differences are also evident. In some provinces, the removal of Francoist names from street directories was already underway before the HML came into effect. In others, implementation was delayed. Electoral cycles and local disagreements with the law may have played a significant role in these disparities. At the time of the repeal of Law 52/2007 by the new Democratic Memory Law (Law 20/2022), the Administrative Chamber of the Spanish Supreme Court had published a total of 12 rulings and judgments related to the HML[ 14 ]. References to Francisco Franco and José Antonio Primo de Rivera have been widely removed across the entire national territory. The same applies to other major figures associated with Francoism. However, significant differences exist regarding names that were replaced less frequently. Some of these differences stem simply from the fact that not all places had the same references. Others may be linked to the application of varying removal criteria. Individuals from the cultural sphere included in the lists provide a clear example. The Madrid City Council publicly stated that it would not remove streets named after Salvador Dalí, a widely popular artist. Nevertheless, in 2021 Spain had 8,131 municipalities, and not all followed the same criteria; nor were these criteria applied uniformly across all artists. Regarding the legal interpretation of the law, a Supreme Court ruling from April 27, 2022 (ATS 6259/2022) still refers to the need to clarify the "scope and meaning of the concept of personal or collective exaltation" mentioned in Article 15.1 of Law 52/2007, highlighting the ongoing relevance of this issue for jurisprudence[ 15 ]. The effects of the HML have important implications for understanding the dynamics of street name changes. Toponymy in a given locality typically depends on local sociocultural characteristics [ 5 ]. However, as demonstrated by the changes linked to the HML, broader factors—extending beyond the boundaries of individual municipalities—also influence toponymic practices. The observed differences in re-toponymization processes suggest the existence of a political geography of toponymy [ 16 ]. The ability to analyze time series of street name changes at the street-level enables a spatio-temporal approach across multiple scales and in relation to various variables—such as the political orientation of local governments and parliamentary support for the HML. In other words, the data reflect how the country is governed: governance, both across territories and at the administrative level. Declarations Conflict of Interest The authors declare no conflicts of interest. Data Availability Statement The datasets analyzed in this study are all from official Spanish public datasets INE. Instituto Nacional de Estadística: https://www.ine.es/en/ Ethical Approval This study is a historical humanities and social science research, and does not involve any research content that requires ethical approval, as follows: The research objects are historical documents, archival materials and published historical data, and do not involve human subjects, in vivo studies, animal experiments or the use of human tissues. The research process does not involve any behavior that may infringe on personal privacy, cultural rights, or ethical norms, and does not require ethical norms involving human or animal research, such as the Declaration of Helsinki. Based on the ethical requirements of HSSC for humanities and social science research, this study was not submitted to the Ethical Review Committee for approval because there were no relevant ethical risk points, and it complied with the journal's submission regulations of "non-applicable research must be clearly stated". I nformed Consent Informed consent is not required for this study based on the following: The core content of the research is historical events, literature interpretation and historical data combing, and does not involve interactive research behaviors such as recruitment, interviews, and surveys of contemporary human participants. The information about historical figures involved in the study is all from public historical records, and there are no clearly identifiable individual or their legal heirs, so there is no risk of infringing on personal privacy or rights. If a small number of private records of modern and modern identifiable individuals (such as diaries and letters) are cited in the study, key identifying information has been anonymized, and the citation behavior is in accordance with copyright law and the ethics of using historical materials, and no additional informed consent is required. Author Contribution Author Contributions: Conceptualization, S.E.R.; Methodology, S.E.R., Z.L.; Software, S.E.R., Z.L.; Validation, S.E.R., Z.L.; Formal analysis, S.E.R., Z.L.; Investigation, S.E.R., Z.L.; Resources, S.E.R., Z.L.; Data curation, S.E.R., Z.L.; Writing—original draft preparation, S.E.R., Z.L.; Writing—review and editing, S.E.R., Z.L.; Translation, Z.L.; Visualization, S.E.R., Z.L.; Supervision, S.E.R., Z.L.; Project administration, S.E.R. References Jefatura del Estado (2022) Ley 20/2022, de 19 de octubre, de Memoria Democrática. En Boletín Oficial del Estado, núm. 252, de 20/10/2022. Recuperado de https://www.boe.es/eli/es/l/2022/10/19/20/con Jefatura del Estado (2007) Ley 52/2007, de 26 de diciembre, por la que se reconocen y amplían derechos y se establecen medidas en favor de quienes padecieron persecución o violencia durante la guerra civil y la dictadura. En Boletín Oficial del Estado, núm. 310, de 27/12/2007. Recuperado de https://www.boe.es/eli/es/l/2007/12/26/52/con García-Álvarez J (2009) Lugares, paisajes y políticas de memoria. Una lectura geográfica. Boletín De La Asociación De Geógrafos Españoles, (51). Recuperado de https://bage.age-geografia.es/ojs/index.php/bage/article/view/1137 Izu-Belloso MJ (2010) La toponimia urbana en el derecho español. Revista de administración pública, (181), 267–300. Recuperado de https://recyt.fecyt.es/index.php/RAP/article/view/45774 Oto-Peralías D (2018) What do street names tell us? The ‘city-text’ as socio-cultural data. J Econ Geogr 18(1):187–211. 10.1093/jeg/lbx030 INE (2001–2021) Callejero Censo Electoral. En Instituto Nacional de Estadística. Recuperado de https://www.ine.es/ss/Satellite?L=es_ES&c=Page&cid=1259952026632&p=1259952026632&pagename=ProductosYServicios%2FPYSLayout de Andrés-Sanz J (2006) Los símbolos y la memoria del Franquismo. Recuperado de https://www.almendron.com/tribuna/wp-content/uploads/2007/01/los-simbolos-y-la-memoria-del-franquismo.pdf Ayuntamiento de Madrid (2017) Informe propuesta del comisionado de memoria histórica sobre revisión del callejero del Ayuntamiento de Madrid. Recuperado de https://www.madrid.es/UnidadesDescentralizadas/UDCPleno/CentroDocumentacion/DocComisionado/2%20Informe_Propuesta_Comisionado_Revisi%C3%B3n.pdf Casa de la República (2022) Memoria sobre los signos del franquismo mantenidos a día de hoy en Carmona. Foro por la Memoria de Andalucía. Recuperado de https://todoslosnombres.org/wp-content/uploads/2022/01/documento541_0.pdf Bird S, Klein E, Loper E (2009) Natural Language Processing with Python. Analyzing Text with the Natural Language Toolkit. Retrieved from https://www.nltk.org/book Tavenard, R., Faouzi, J., Vandewiele, G., Divo, F., Androz, G., Holtz, C., … Woods,E. (2020). Tslearn, A Machine Learning Toolkit for Time Series Data. Journal of Machine Learning Research, 21 (118), 1–6. Recuperado de http://jmlr.org/papers/v21/20-091.html Mueller A (2020) WordCloud for Python documentation. Recuperado de https://amueller.github.io/word_cloud/index.html García-Álvarez J (2009) Lugares, paisajes y políticas de memoria. Una lectura geográfica. Boletín De La Asociación De Geógrafos Españoles, (51). Recuperado de https://bage.age-geografia.es/ojs/index.php/bage/article/view/1137 Consejo General del Poder Judicial (2022) Buscador, CENDOJ (Centro de Documentación Judicial). En Consejo General del Poder Judicial. Recuperado de https://www.poderjudicial.es/search/ Requero Ibañez JL (2022) ATS 6259/2022. En Consejo General del Poder Judicial. Recuperado de https://www.poderjudicial.es/search/TS/openDocument/028531ca14e896fa/20220503 Esteban Rodríguez S (2023) Procesos de retoponimización en España. Semestrale di Studi e Ricerche di Geografia, vol 1. XXXV, pp 45–51. 10.13133/2784-9643/18287 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8622574","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":581646315,"identity":"16859ac3-0ed5-450d-a641-e55361f0ee90","order_by":0,"name":"Samuel Esteban Rodríguez","email":"","orcid":"","institution":"University of Zaragoza","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"Esteban","lastName":"Rodríguez","suffix":""},{"id":581646316,"identity":"80cc0258-41fc-4c0c-93a0-a6868264f630","order_by":1,"name":"Zhaoyang Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIie2PsQrCMBRFXyikDoWuhuI/BJyEUv2UhkBnx44PuhZcK/gR3cQtksGl2LXSSfyC4qAuamcRYjeHnP1wzwWwWP4Q313d7t0zBHB+VViuOCtoMkDhzYIHI6oHhLEC4il4tdi67vmaQjg3Kn6ASi7HrdhlIFkFiUDjymaPuuCtKDUohqBj4wpvJMm8+NgrJHsgvMxhvEkcx1OqVxzaryhiDssrStYop6WmdIZcmr/4bk6hw2hS1ofLCdPIHPbZOVSwWCwWy1fe8Po9zQ78oh4AAAAASUVORK5CYII=","orcid":"","institution":"University of Zaragoza","correspondingAuthor":true,"prefix":"","firstName":"Zhaoyang","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-01-16 23:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8622574/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8622574/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101485149,"identity":"6d73b944-c2e3-4acb-bdc4-7eb335330cf7","added_by":"auto","created_at":"2026-01-30 08:58:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51125,"visible":true,"origin":"","legend":"\u003cp\u003eStreet map of the Electoral Census. Own elaboration.\u003c/p\u003e","description":"","filename":"Figures1.png","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/4835af0543ab242bcd3f24a0.png"},{"id":101485072,"identity":"18501c59-67ea-4314-9fc4-2cd2d62028e6","added_by":"auto","created_at":"2026-01-30 08:57:48","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":193011,"visible":true,"origin":"","legend":"\u003cp\u003eStreet map of the Electoral Census and cartographic bases of the National Geographic Institute. Own elaboration.\u003c/p\u003e","description":"","filename":"Figures2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/cbb9422d7cd1707f3afc6e74.jpg"},{"id":101485120,"identity":"fc8b7654-f8bc-4584-9ea9-6d78a11d3500","added_by":"auto","created_at":"2026-01-30 08:57:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40295,"visible":true,"origin":"","legend":"\u003cp\u003eStreet map of the Electoral Census. Own elaboration.\u003c/p\u003e","description":"","filename":"Figures3.png","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/0ea8a25aa203ace6dc800ab9.png"},{"id":101485054,"identity":"d5b13e71-2ef9-41b8-8619-f90bc053b020","added_by":"auto","created_at":"2026-01-30 08:57:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":29587,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of streets whose names have changed in application of Law 52/2007 between 2001 and 2021, by autonomous communities\u003c/p\u003e\n\u003cp\u003eFuente: Callejero del Censo Electoral. Elaboración propia.\u003c/p\u003e","description":"","filename":"Figures4.png","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/5b9abb8b7f823b995ab08669.png"},{"id":101485100,"identity":"9bcdde89-376f-40a8-8b27-9bf487a5b1a8","added_by":"auto","created_at":"2026-01-30 08:57:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":411990,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of streets susceptible to re-onimisation by Law 52/2007 that have effectively changed their name between 2001 and 2021\u003c/p\u003e\n\u003cp\u003eFuente: Callejero del Censo Electoral y bases cartográficas del Instituto Geográfico Nacional. Elaboración propia.\u003c/p\u003e","description":"","filename":"Figures5.png","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/50de7e99af5d06c7b0450d8a.png"},{"id":101485101,"identity":"b210ad92-6a25-4793-889f-731725ae0757","added_by":"auto","created_at":"2026-01-30 08:57:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":404714,"visible":true,"origin":"","legend":"\u003cp\u003eGroups of provinces according to the development of the re-ponymization process in application of Law 52/2007\u003c/p\u003e\n\u003cp\u003e* P: evolución acumulada de las provincias del grupo. E: centros del clúster del grupo\u003c/p\u003e\n\u003cp\u003eFuente: Callejero del Censo Electoral y bases cartográficas del Instituto Geográfico Nacional. Elaboración propia.\u003c/p\u003e","description":"","filename":"Figures6.png","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/19fa31056713af9a4132783d.png"},{"id":101485139,"identity":"13233058-d485-4d88-866e-e96332521763","added_by":"auto","created_at":"2026-01-30 08:57:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":57437,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of the re-on-the-moxisation process in application of Law 52/2007 by groups\u003c/p\u003e\n\u003cp\u003eof provinces\u003c/p\u003e\n\u003cp\u003eSource: Street Map of the Electoral Census. Own elaboration.\u003c/p\u003e","description":"","filename":"Figures7.png","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/ceb9a0868994a55a4b8a8eee.png"},{"id":101485105,"identity":"d225e347-6e70-43fe-b320-a88e8e2943b4","added_by":"auto","created_at":"2026-01-30 08:57:52","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":47902,"visible":true,"origin":"","legend":"\u003cp\u003eCloud of the most frequent words of the streets repurposed in application of Law 52/2007\u003c/p\u003e","description":"","filename":"Figures8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/299fa198a36c3949b1a610d5.jpg"},{"id":104564000,"identity":"3fa7742e-83d2-4a92-a223-fd711c9a89c1","added_by":"auto","created_at":"2026-03-13 10:56:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1783748,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8622574/v1/5ab5fb47-2722-40bd-9689-13ca8dd0555f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Historical Memory Law and Retoponimization Processes in Spain","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn Spain, the publication in the Official State Gazette (BOE) of Law 20/2022, of 19 October, on Democratic Memory[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] marked a new phase in the legal treatment of collective memory regarding the Spanish Civil War and the subsequent dictatorship of Francisco Franco. Fifteen years had passed since the approval of Law 52/2007, of 26 December, better known as the Historical Memory Law (HML), which recognized and extended rights and established measures in favor of those who suffered persecution or violence during the Civil War and the dictatorship [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The repeal of this law with the entry into force of Law 20/2022 provides a timely opportunity to assess its implementation over the period since its enactment.\u003c/p\u003e \u003cp\u003eLaw 52/2007 established the obligation to remove from public spaces any symbols, plaques, or references that glorified the 1936 military uprising, the Civil War, or the subsequent Franco dictatorship (Article 15). As stated in its preamble, the law aimed to transform public space into a shared space of encounter and memory for citizens. To achieve this goal, public administrations were required to remove all personal and collective references that, in any way, amounted to an exaltation of the Franco regime (Article 15). Failure to comply could result in sanctions such as the withdrawal of public subsidies and grants\u0026mdash;measures to which local authorities are particularly sensitive.\u003c/p\u003e \u003cp\u003eThere are strong connections between geographical space and memory [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Consequently, processes of toponymic change (re-toponymization) and interventions in the symbolic use of street names are not new in Spain. In other historical periods, street name changes have also occurred by legal mandate. One such process was initiated by Franco\u0026rsquo;s government during and after the Civil War, during which numerous references from the liberal period and nearly all from the Republican era were removed and replaced with names honoring values, events, and figures from the Francoist side [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In some municipalities, these names were changed at the beginning of the transition to democracy; however, in others, much of this nomenclature remained in place .\u003c/p\u003e \u003cp\u003eThe naming and labeling of streets fall under municipal authority [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Nevertheless, certain traditional limitations have applied to this municipal autonomy: for example, the use of names that glorify criminal acts such as terrorism is not permitted, nor are names that violate public principles or morality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. To these constraints were added those introduced by Law 52/2007, now incorporated into Article 35 of Law 20/2022, which, like its predecessor, applies uniformly across the entire national territory.\u003c/p\u003e \u003cp\u003eGiven the national scope of the HML, one might expect a homogeneous application across the country. However, in substance, there are varying degrees of sensitivity among the Spanish population\u0026mdash;and among the political groups governing each administration. As was the case with Law 20/2022, the HML was not approved unanimously by the Cortes Generales (nor even by a broad majority) and was criticized for imposing a single version of history. Its implementation has also been controversial [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore, given the distribution of competences over this matter, territorial differences in the law\u0026rsquo;s application and its impact on street nomenclature are likely. Since the HML lacks transitional provisions and does not provide a specific list of names to be removed, these differences may manifest in at least three ways:\u003c/p\u003e \u003cp\u003eThe timing of implementation, the number of streets with references to the Franco regime that were removed, and the specific individuals and events to which these references pertain.\u003c/p\u003e \u003cp\u003eThis study focuses on analyzing these three dimensions. Using the Street Directory of the Electoral Census (CCE) published by the National Institute of Statistics (INE) as the primary data source, we have examined changes in street names containing references that could be subject to removal under the HML. The study period spans from 2001 to 2021, and the analysis is conducted at the national, autonomous community, and provincial levels. The methodology section details the research procedures. The results section first presents the situation in 2001, followed by the evolution of aggregated data and a characterization of provinces according to the number of streets related to the Franco regime that were removed at different times. Finally, the frequency distribution of the affected references is analyzed. A discussion section follows the results, and the paper concludes with a summary of the main findings.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003eThe study of street names allows for the characterization of social space [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In relation to the subject of this study, it enables the identification and quantification of nomenclature associated with the Franco regime. The Street Directory of the Electoral Census (CCE) published by the National Institute of Statistics (INE) provides the names of all streets in Spain on a regular basis; since 2007, it has been semiannual. Before 2007, the periodicity was annual until 2004, and prior to 2004, only the street directory of July 2001 is available for free download. The CCE assigns a unique identifier to each street. In different publications, along with this identifier, the name of the street is included if it exists. Monitoring the names of each street allows identifying which ones have changed. This has been done for all streets in Spain across all directories published between July 2001 and July 2021 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Identification of Name Changes Linked to Law 52/2007\u003c/h2\u003e \u003cp\u003eNot all changes in street names are significant, nor can they all be linked to the Historical Memory Law (HML). Frequently, modifications relate to minor variations in the spelling of names; for example, those resulting from the use or omission of abbreviations. Additionally, parallel to the implementation of Law 52/2007, other processes of re-toponymization occur in Spain. Notably, these include those related to the country's multilingual reality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; that is, the translation of names into various regional languages. In such cases,the changes are primarily linguistic rather than ideological. For instance, a street named \"Calle de Jos\u0026eacute; Antonio\" might be translated to \"Carrer de Josep Antoni\" in Catalan regions without altering its reference to a figure associated with the Franco regime. Therefore, distinguishing changes driven by the HML from those arising from linguistic adaptation or other local initiatives requires careful analysis.\u003c/p\u003e \u003cp\u003eTo focus the study on name changes related to Law 52/2007, streets with names potentially subject to the application of its Article 15 were first identified. As previously noted, Law 52/2007 does not include an annex listing names to be removed, nor has it been developed through regulatory provisions. In reality, there is no official and exhaustive list of names to be removed. Therefore, the names potentially subject to this law have been drawn from lists published in various studies on the topic. These include those by[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], the proposal report by the Madrid City Council's Historical Memory Commissioner on street name review [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], the database from Deberiadesaparecer.com (2020), the report on Francoist symbols in Carmona, Seville[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the list of towns in the province of \u0026Aacute;vila with Francoist-related nomenclature published by Foro por la Memoria (n.d.), and the lists of officers from Franco\u0026rsquo;s army published on Combatientes.es (n.d.). Additionally, the most frequent names appearing in streets that have undergone renaming were reviewed, and a list was constructed of those identified as linked to the Franco regime. These name sources were consolidated into a single list to eliminate duplicates. This unified list was then used to identify the presence of references related to Francoism in street names.\u003c/p\u003e \u003cp\u003eSubsequently, their evolution was analyzed by examining the degree of similarity between the names of the same street in two consecutive street registries. Data on streets with references to the Franco regime were aggregated at the provincial, regional, and national levels, along with the total number of streets for each date. This information was used to group provinces according to their trends, derive statistics, and produce cartographic representations. The following steps were followed.\u003c/p\u003e \u003cp\u003eStreet registries from the 34 different dates previously specified were processed. The average number of streets per registry is 847,964; in total, 28,830,791 street names were analyzed. Tracking the name of each street was carried out using similarity measures, applying a comparison methodology based on trigrams. This technique, frequently used in natural language processing [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], involves decomposing names into recursive combinations of three characters, or trigrams. A string similarity index aligned with those implemented by Bird et al. (2009)[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] was used. The index (S) is calculated as the product of two ratios [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]: when comparing street names at two different points in time, the first ratio is the number of common trigrams (C) divided by the number of trigrams in the name at time 1 (T1); the second ratio is the number of common trigrams divided by the number of trigrams in the name at time 2 (T2). In this index, a value of 1 indicates complete similarity, while a value of 0 indicates no similarity, which occurs when both strings share no trigrams. Based on this similarity index, a complementary distance index (D) was derived; this is understood as the amount needed to reach the maximum similarity value, i.e., D\u0026thinsp;=\u0026thinsp;1 \u0026ndash; S [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSubsequently, their evolution was studied by examining the degree of similarity between the names of the same street in two consecutive street registries. Data on streets with references to the Franco regime were aggregated at the provincial, regional, and national levels, along with the total number of streets for each date. This information was used to group provinces according to their trends, and to derive statistics and cartographic representations. The following steps were then carried out.\u003c/p\u003e \u003cp\u003eThe street registries from the 34 different dates previously specified were processed. The average number of streets per registry is 847,964; in total, 28,830,791 street names were analyzed. The tracking of each street's name was performed using similarity measures, applying a comparison methodology based on trigrams. This technique, commonly used in natural language processing [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], involves decomposing names into recursive three-character combinations, or trigrams. A string similarity index consistent with those implemented by Bird et al. (2009) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] was used. The index (S) is calculated as the product of two ratios [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]: when comparing street names at two different points in time, the first ratio is the number of common trigrams (C) divided by the number of trigrams in the name at time 1 (T1); the second ratio is the number of common trigrams divided by the number of trigrams in the name at time 2 (T2). In this index, a value of 1 indicates complete similarity, while a value of 0 indicates no similarity, which occurs when both strings share no trigrams. Based on this similarity index, a complementary name distance index (D) was derived; this is understood as the amount that must be subtracted from the similarity index to reach its maximum value.\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:S=\\frac{C}{{T}_{1}}\\:\u0026middot;\\:\\frac{C}{{T}_{2}}\\:\\)\u003c/span\u003e \u003c/span\u003e[1]\u003c/p\u003e \u003cp\u003eD\u0026thinsp;=\u0026thinsp;1 - S [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTo detect street name changes, the denomination of each street in a given census edition was compared with its name in the subsequent edition. This comparison was performed using a string distance index. Prior to calculation, text strings were cleaned by removing special characters such as diacritical marks and punctuation. Streets whose names exhibit a distance greater than zero correspond to those that have undergone some form of change. However, many of these changes are minor. To focus the study on significant changes, a minimum distance threshold of 0.2 was established.\u003c/p\u003e \u003cp\u003eUsing 2001 as the reference year and applying a similarity index (S), streets showing any resemblance to names from the list of terms associated with Francoism were identified. These names were then aggregated and reviewed to exclude entries that could introduce ambiguity when detecting associations. After this refinement, streets were considered as bearing names potentially subject to the Historical Memory Law if they exhibited a similarity index greater than 0.8 with any name on the reference list.\u003c/p\u003e \u003cp\u003eA mention was considered removed when a street\u0026rsquo;s name underwent significant changes or when the street was officially decommissioned. Regarding the latter, a street was deemed decommissioned if its unique identifier ceased to appear in subsequent censuses. Removed mentions were assigned to the intercensal period preceding the one in which the change was detected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data Analysis\u003c/h2\u003e \u003cp\u003eStreets containing references to the Franco regime in 2001, along with their changes in each successive directory, were aggregated at the provincial, autonomous community, and national levels, computed annually. The same aggregation was applied to the total number of streets in each census and to the number of distinct streets derived from merging all editions.\u003c/p\u003e \u003cp\u003eWith respect to 2001, the percentage of streets referencing Francoism relative to the total number of streets that year was calculated. In subsequent years, we counted the number of Francoist references from 2001 that had been replaced. This information was used to construct a time series tracking the behavior of each territorial unit over time, enabling the identification of growth patterns and the clustering of provinces with similar trajectories.\u003c/p\u003e \u003cp\u003eProvinces were grouped into four clusters using clustering algorithms implemented by Tavenard et al. (2021) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] in the tslearn library. Clustering was performed using cumulative values. Similarity between time series was measured using Dynamic Time Warping (DTW), a time-series alignment algorithm particularly suited for sequences with temporal shifts. The clustering results were mapped to analyze their geographical distribution, supplemented by data on the timing of changes in each unit and the number of streets replaced.\u003c/p\u003e \u003cp\u003eThe actual names of removed references were subjected to a frequency analysis at both national and cluster levels. To perform this, replaced street names were grouped by comparing all string pairs using the similarity index. The goal of this grouping was to determine how many streets referred to each individual figure or historical event. To minimize double-counting, replaced names appearing in the lists were considered linked to the same entity if their pairwise similarity index was equal to or greater than 0.5. The resulting groups were manually reviewed, and references to the same person not captured by the initial filter were re-grouped accordingly.\u003c/p\u003e \u003cp\u003eFor example, in the case of Franco, references included his full name, surname, military rank, honorific titles such as caudillo and generalissimo, as well as common variants. After grouping, the frequency of each reference was analyzed. Additionally, to provide a synthetic visual overview, a word cloud of the most frequently removed street names was generated using tools developed by[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eUsing the methodology described, it is estimated that in the year 2001, across Spain as a whole, the number of streets subject to toponymic change under Article 15 of Law 52/2007\u0026mdash;i.e., streets with names associated with the Franco regime\u0026mdash;was 10,147. This represented approximately 1.33% of all streets nationwide. Regions with the lowest proportions were the Basque Country, Catalonia, and the Balearic Islands; at the opposite end of the spectrum were Castilla-La Mancha, Extremadura, and Castile and Le\u0026oacute;n (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the same variable in cartographic format, but at the provincial scale. There is a high concentration of streets whose names should change in all the provinces of the interior of Spain, both in both plateaus and in the Ebro Valley, with the only exception of Huesca. Its presence is also high in the Canary Islands, Cantabria and Murcia, as well as in some provinces of other coastal regions [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In the rest of the territory the proportion of streets linked to the Franco regime was smaller, especially in the Catalan and Basque provinces.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1. The process of re-ponymization in application of the Law of Historical Memory\u003c/h2\u003e \u003cp\u003eThe number of streets repurposed in relation to the LMH between 2001 and 2021 has been 4931. The modification of the street gazetteer has taken place throughout the period considered, although, in Spain as a whole, there are two stages in which the number of changes is particularly high: the first occurs immediately after the approval of the regulation, in 2008; the second, which is when the most changes take place, around 2017 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Between the two, there is a stage in which the rate of retoponymization decreases; In the last years of the series, the number of name changes also decreases.\u003c/p\u003e \u003cp\u003eAt the level of the Autonomous Communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), the changes are of lesser volume in those that had a lower presence of names susceptible to re-on-ponymization in 2001. In this regard, both Catalonia and the Basque Country are paradigmatic cases, although the evolution is also similar in other regions such as Andalusia. At the other extreme, in that of the regions with the most changes, the 3 communities that in 2001 had a higher proportion of names related to the Franco era stand out.\u003c/p\u003e \u003cp\u003eAt the scale of the provinces, the high proportion of changes that have occurred in the inland areas bordering Portugal is striking, with the axis formed by Zamora, Salamanca and C\u0026aacute;ceres clearly standing out (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These provinces, in line with what was observed at the regional level, had a high proportion of names related to the Franco regime in 2001. This direct relationship between the number of streets with mentions of Francoism and the number of streets re-established is the general pattern in the period that has been analysed. Despite this, there are some provinces that have particularities. We can mention the case of Asturias, where the concentration of streets related to the Franco regime was low in 2001 and, however, the proportion of changes between 2001 and 2021 is high. For their part, in the autonomous cities, the proportion of streets repurposed has been high in Melilla.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Groups of provinces based on detected name changes\u003c/h2\u003e \u003cp\u003eBased on the time series of the cumulative number of streets repurposed in application of Law 52/2007, the following 4 groups of provinces can be defined (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe first group corresponds to provinces in which the cumulative number of changes has been very high. Salamanca, C\u0026aacute;ceres and Toledo are located there. Unlike what has been observed in Spain as a whole, since the approval of the law, this group has 3 moments in which, as can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the changes are numerous. These occur around the years 2009, 2015 and 2018.\u003c/p\u003e \u003cp\u003eThe second group is mainly made up of provinces in the interior with a high concentration of names in 2001; by way of example, it is worth mentioning cases such as Madrid, Valladolid or Zaragoza. In these provinces, the process of re-ponymization has been intense, although of lesser importance than in the previous group. Despite this, it is a larger group of provinces and, in aggregate terms, has a greater number of streets revisited (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Its evolution presents cycles of retoponimization similar to those observed in Spain as a whole.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of provinces and number of streets renamed by groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvince groups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of provinces\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of streets repurposed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChanges in total (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23,69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29,73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33,54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13,04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100,00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe third group is the one with the largest number of streets with mentions of the Franco regime re-ponymized, although the average per territorial unit is lower than in the previous ones. It is made up of 18 provinces from different regions; for example, Cantabria, Le\u0026oacute;n, Burgos, Navarra, Teruel, Valencia or Seville. Although the evolution of the group presents similar stages to those of the country as a whole, the proportion of streets re-ponymized in each phase presents singularities. In this group, in the years immediately following the implementation of the law of historical memory, the proportion of streets repurposed was very high. In addition, it has a less accentuated but longer second growth phase.\u003c/p\u003e \u003cp\u003e4) The fourth and last group is the one with the largest number of provinces. However, it has had fewer changes than the others. It includes all the provinces of the Canary Islands, Galicia, the Basque Country and Catalonia, most of Andalusia and also the provinces of Asturias, Huesca, Soria and Castell\u0026oacute;n. In all of them, except for the Canary Islands and some Galician provinces, the concentration of streets with names referring to the Franco regime was low in 2001. Its evolution, in cumulative terms, presents a little steep slope. In this group, the evolution of the number of replacements is different from that of the previous ones, which concentrate most of the modifications in the second period of re-on-the-top. In the fourth group there are fewer changes and those that do occur have their maximum peak just after the approval of the law.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Replaced toponyms\u003c/h2\u003e \u003cp\u003eIn application of the Law of Historical Memory, the names that have been replaced most frequently are those referring to Franco himself, which account for 17.73% of the total. Among the streets that have been renamed, those referring to Jos\u0026eacute; Antonio Primo de Rivera are also very numerous; This is approximately 14.79% of those that have been modified. These, plus those that allude to General Mola, Calvo Sotelo and Salas Pombo, account for more than 50% of the changes. In total, modifications have been detected referring to 674 events or characters. The 26 names that have been replaced most frequently account for approximately 80% of the changes.\u003c/p\u003e \u003cp\u003eIn all the groups of provinces, the two names that have withdrawn the most coincide with those of Spain as a whole (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, in other cases, the relative frequency and order of occurrence vary in each area. It is worth highlighting the case of Salas Pombo, numerous in the provinces of group 1, but without significant equivalences in the rest; In this group, the changes recorded affect a smaller number of names than in the rest (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, the diversity of replaced names is much greater in the fourth group, despite having fewer changes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNames most frequently replaced in application of Law 52/2007\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProportion in\u003c/p\u003e \u003cp\u003eSpain (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eGroups of provinces\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrancisco Franco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17,73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5,54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJos\u0026eacute; Antonio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14,79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Mola\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3,39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalvo Sotelo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePombo Rooms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Street Map of the Electoral Census. Own elaboration\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNames and streets most frequently revisited in application of Law 52/2007\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroups (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNames (2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStreets (3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubstitutions (4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDiversity (5)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13,58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7,36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16,51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24,57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13,67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: (1) Groups of provinces. (2) Number of names replaced. (3) Number of streets retoponymized. (4) Average number of changes per name (5) Number of different names / Number of changes (%)\u003c/p\u003e \u003cp\u003eSource: Street Map of the Electoral Census. Own elaboration\u003c/p\u003e \u003cp\u003eIn the replaced names, the mentions of the army are numerous. Due to their high frequency, those made to generals and senior commanders stand out (Fig.\u0026nbsp;8). In this group, in addition to those referring to Franco -who was a general-, there are many others. In addition to the mentions of the generalship, there are a high number of references to the rest of the officer corps, combatants of Franco's army and volunteers of the Blue Division. The names of battles and allusions to those who fell in combat are also frequent. In all cases there are names of specific people, places, dates and events. Although some references to individual soldiers appear on the streets that have been renamed, these are usually grouped under certain slogans; for example, Defensores de Oviedo. In any case, the references to the troops in the street are much less numerous than the references to the officers. Among the events are battles, such as the Ebro and the siege of the Alc\u0026aacute;zar of Toledo. In terms of dates, references to July 18, 1936 are the most numerous. In relation to casualties, the combatants who died and the people executed by militiamen on the Republican side are usually given generic names: the former fallen and the latter martyrs.\u003c/p\u003e \u003cp\u003eIn the replaced personal names, masculine names predominate; among women's pensions, that of Pilar Primo de Rivera has been the one that has been replaced on a greater number of occasions. In areas of social life other than military confrontation and politics, references to people from the world of culture have been eliminated, such as the painter Salvador Dal\u0026iacute;, the writer Mu\u0026ntilde;oz Seca or the composer Manuel de Falla; although, among these, as in the case of politicians active during democracy, the frequency of re-ponymization is low; approximately 2.55% compared to 48.72% for all names present in 2001. Although in the last street map that has been analysed there are some references to relevant figures of the Franco regime, their number is very small in relation to 2001. Most of the references to names present in the lists that survive correspond to characters from the world of culture.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn relation to the methodology used and in line with the work of Oto-Peral\u0026iacute;as (2017), it is worth noting the usefulness of the electoral census street map as a source of information on toponymy and, more specifically, its usefulness in identifying changes in it.\u003c/p\u003e \u003cp\u003eThe use of natural language processing techniques and similarity indices makes it possible to work with this data source, especially when the study area includes a large number of streets and the temporal scope is long, as is the case of this work. Despite this, the search for correspondences and variations presents some difficulties. One of the most problematic issues is the establishment of similarity and distance thresholds, as they are directly related to errors of omission and commission.\u003c/p\u003e \u003cp\u003eAs for the sources of names of people and events related to Francoism, the lists with the greatest scope that have been handled are the lists of army officers. Although attempts have been made to integrate different sources of information, these are not sufficiently exhaustive lists. It should be noted that, in the requests for the removal of streets submitted to the municipalities with which we have worked, relatively anonymous people appear with some frequency; The most typical cases are those of people who were members of a political party and town mayors whose mention some historical memory association requested to withdraw. In this work, there has not been an exhaustive list of public officials from the Franco era. Therefore, the total number of changes may vary in relation to that observed in the results.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe results obtained reveal that the implementation of the Historical Memory Law (HML) has been intense. Approximately 5,000 streets in Spain have been renamed over a period of just 15 years as a direct consequence of the law. The HML has removed numerous references to the country\u0026rsquo;s history prior to the establishment of the current democratic system from public space.\u003c/p\u003e \u003cp\u003eOn many occasions, critics\u0026mdash;particularly those who opposed the law\u0026rsquo;s approval\u0026mdash;have argued that this process constitutes an attempt to rewrite history. However, as highlighted by Garc\u0026iacute;a-\u0026Aacute;lvarez (2009) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and Izu-Belloso (2010) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], many of these streets had previously been renamed during Franco\u0026rsquo;s dictatorship and in earlier political transitions. In this sense, it can be asserted that processes of re-toponymization have occurred frequently throughout Spain\u0026rsquo;s contemporary history.\u003c/p\u003e \u003cp\u003eRegarding whether the application of the law has been homogeneous, the answer is clearly no. As demonstrated in the results, there are significant differences across regions, evident in all aspects analyzed: the number of streets renamed, the timing of implementation, and the names replaced.\u003c/p\u003e \u003cp\u003eIn terms of the number of renamed streets, the impact of the law has varied considerably across the territory. This variation largely depended on the number of streets bearing Francoist references at the time the law came into force. The most affected areas were the inland provinces of Spain, which preserved the highest number of such references. In contrast, regions such as Andalusia, the Basque Country, and Catalonia experienced a smaller impact. In these regions and in many cities, references to the main figures of Francoism were already removed at the beginning of the current democratic period[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith regard to the timing of implementation, significant differences are also evident. In some provinces, the removal of Francoist names from street directories was already underway before the HML came into effect. In others, implementation was delayed. Electoral cycles and local disagreements with the law may have played a significant role in these disparities. At the time of the repeal of Law 52/2007 by the new Democratic Memory Law (Law 20/2022), the Administrative Chamber of the Spanish Supreme Court had published a total of 12 rulings and judgments related to the HML[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eReferences to Francisco Franco and Jos\u0026eacute; Antonio Primo de Rivera have been widely removed across the entire national territory. The same applies to other major figures associated with Francoism. However, significant differences exist regarding names that were replaced less frequently. Some of these differences stem simply from the fact that not all places had the same references. Others may be linked to the application of varying removal criteria. Individuals from the cultural sphere included in the lists provide a clear example. The Madrid City Council publicly stated that it would not remove streets named after Salvador Dal\u0026iacute;, a widely popular artist. Nevertheless, in 2021 Spain had 8,131 municipalities, and not all followed the same criteria; nor were these criteria applied uniformly across all artists. Regarding the legal interpretation of the law, a Supreme Court ruling from April 27, 2022 (ATS 6259/2022) still refers to the need to clarify the \"scope and meaning of the concept of personal or collective exaltation\" mentioned in Article 15.1 of Law 52/2007, highlighting the ongoing relevance of this issue for jurisprudence[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe effects of the HML have important implications for understanding the dynamics of street name changes. Toponymy in a given locality typically depends on local sociocultural characteristics [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, as demonstrated by the changes linked to the HML, broader factors\u0026mdash;extending beyond the boundaries of individual municipalities\u0026mdash;also influence toponymic practices.\u003c/p\u003e \u003cp\u003eThe observed differences in re-toponymization processes suggest the existence of a political geography of toponymy [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The ability to analyze time series of street name changes at the street-level enables a spatio-temporal approach across multiple scales and in relation to various variables\u0026mdash;such as the political orientation of local governments and parliamentary support for the HML. In other words, the data reflect how the country is governed: governance, both across territories and at the administrative level.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed in this study are all from official Spanish public datasets\u003c/p\u003e\n\u003cp\u003eINE. Instituto Nacional de Estadística: https://www.ine.es/en/\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is a historical humanities and social science research, and does not involve any research content that requires ethical approval, as follows:\u003c/p\u003e\n\u003cp\u003eThe research objects are historical documents, archival materials and published historical data, and do not involve human subjects, in vivo studies, animal experiments or the use of human tissues.\u003c/p\u003e\n\u003cp\u003eThe research process does not involve any behavior that may infringe on personal privacy, cultural rights, or ethical norms, and does not require ethical norms involving human or animal research, such as the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eBased on the ethical requirements of HSSC for humanities and social science research, this study was not submitted to the Ethical Review Committee for approval because there were no relevant ethical risk points, and it complied with the journal's \u0026nbsp;submission regulations of \"non-applicable research must be clearly stated\".\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eI\u003cstrong\u003enformed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent is not required for this study based on the following:\u003c/p\u003e\n\u003cp\u003eThe core content of the research is historical events, literature interpretation and historical data combing, and does not involve interactive research behaviors such as recruitment, interviews, and surveys of contemporary human participants.\u003c/p\u003e\n\u003cp\u003eThe information about historical figures involved in the study is all from public historical records, and there are no clearly identifiable individual or their legal heirs, so there is no risk of infringing on personal privacy or rights.\u003c/p\u003e\n\u003cp\u003eIf a small number of private records of modern and modern identifiable individuals (such as diaries and letters) are cited in the study, key identifying information has been anonymized, and the citation behavior is in accordance with copyright law and the ethics of using historical materials, and no additional informed consent is required.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions: Conceptualization, S.E.R.; Methodology, S.E.R., Z.L.; Software, S.E.R., Z.L.; Validation, S.E.R., Z.L.; Formal analysis, S.E.R., Z.L.; Investigation, S.E.R., Z.L.; Resources, S.E.R., Z.L.; Data curation, S.E.R., Z.L.; Writing\u0026mdash;original draft preparation, S.E.R., Z.L.; Writing\u0026mdash;review and editing, S.E.R., Z.L.; Translation, Z.L.; Visualization, S.E.R., Z.L.; Supervision, S.E.R., Z.L.; Project administration, S.E.R.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJefatura del Estado (2022) Ley 20/2022, de 19 de octubre, de Memoria Democr\u0026aacute;tica. 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Recuperado de \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.poderjudicial.es/search/TS/openDocument/028531ca14e896fa/20220503\u003c/span\u003e\u003cspan address=\"https://www.poderjudicial.es/search/TS/openDocument/028531ca14e896fa/20220503\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEsteban Rodr\u0026iacute;guez S (2023) Procesos de retoponimizaci\u0026oacute;n en Espa\u0026ntilde;a. Semestrale di Studi e Ricerche di Geografia, vol 1. XXXV, pp 45\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.13133/2784-9643/18287\u003c/span\u003e\u003cspan address=\"10.13133/2784-9643/18287\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Historical Memory Law, Spain, street nomenclature, toponymy, toponymic change","lastPublishedDoi":"10.21203/rs.3.rs-8622574/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8622574/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn Spain, the state has frequently used street names symbolically: after the Civil War, names associated with the Second Republic, as well as some earlier ones, were re-moved and replaced with those from the so-called Nationalist (or rebel) side. Many of these were later removed after Franco\u0026rsquo;s death; however, some had persisted through-out the democratic period. In 2007, a controversial national Historical Memory Law was passed, mandating the removal of street names that glorify Francoism. The aim of this study is to assess the intensity with which this law has been implemented and to examine potential regional differences. To this end, street name changes across Spain related to the Franco regime between 2001 and 2021 were analyzed, using the Electoral Census Street Directory as the primary data source. The law has led to the widespread removal of names associated with Francoism; however, its impact has not been uni-form across the country, with the highest number of changes occurring in inland provinces.\u003c/p\u003e","manuscriptTitle":"Historical Memory Law and Retoponimization Processes in Spain","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 08:56:48","doi":"10.21203/rs.3.rs-8622574/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":"e9f13cd9-d1b4-4a55-94f6-a413182de914","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61876474,"name":"Humanities/History"},{"id":61876475,"name":"Social science/History"},{"id":61876476,"name":"Social science/Politics and international relations"}],"tags":[],"updatedAt":"2026-03-13T10:56:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 08:56:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8622574","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8622574","identity":"rs-8622574","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}