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  Subjects -> SOCIOLOGY (Total: 553 journals)
Showing 401 - 382 of 382 Journals sorted alphabetically
Tla-Melaua : Revista de Ciencias Sociales     Open Access  
Tracés     Open Access  
Trajecta : Religion, Culture and Society in the Low Countries     Open Access  
Transatlantica     Open Access   (Followers: 2)
Transmotion     Open Access   (Followers: 14)
Transposition : Musique et sciences sociales     Open Access   (Followers: 1)
Travail et Emploi     Open Access   (Followers: 5)
TRIM. Tordesillas : Revista de investigación multidisciplinar     Open Access  
Universidad, Escuela y Sociedad     Open Access   (Followers: 1)
Unoesc & Ciência - ACHS     Open Access  
Urban Research & Practice     Hybrid Journal   (Followers: 23)
Valuation Studies     Open Access   (Followers: 2)
Variations : Revue Internationale de Théorie Critique     Open Access   (Followers: 1)
Visitor Studies     Hybrid Journal   (Followers: 4)
Vlast' (The Authority)     Open Access  
Work, Aging and Retirement     Open Access   (Followers: 4)
World Future Review     Hybrid Journal   (Followers: 1)
Zeitschrift für Religion, Gesellschaft und Politik     Hybrid Journal  

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Sociological Methodology
Journal Prestige (SJR): 1.055
Citation Impact (citeScore): 1
Number of Followers: 21  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0081-1750 - ISSN (Online) 1467-9531
Published by Sage Publications Homepage  [1176 journals]
  • Can Human Reading Validate a Topic Model'

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      Authors: Bolun Zhang, Yimang Zhou, Dai Li
      Abstract: Sociological Methodology, Ahead of Print.
      Validation is at the heart of methodological discussions about topic modeling. The authors argue that validation based on human reading hinges on distinctive words and readers’ labeling of a topic, and it overlooks the probability of conflicting results from semantically similar models, such as regressions or other methods. This runs counter to the presumption that topic modeling can reveal features of documents that have some measurable association with social aspects outside the text. The authors develop a similar topic identifying procedure to verify that semantically similar solutions yield similar results in further analysis. The authors argue that future validations of topic modeling must consider such procedures.
      Citation: Sociological Methodology
      PubDate: 2024-07-25T10:42:32Z
      DOI: 10.1177/00811750241265336
       
  • Using Relative Distribution Methods to Study Economic Polarization across
           Categories and Contexts

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      Authors: Siwei Cheng, Andrew Levine, Ananda Martin-Caughey
      Abstract: Sociological Methodology, Ahead of Print.
      In addition to overall dispersion, the distributional shape of economic status has attracted growing attention in the inequality literature. Economic polarization is a specific form of distributional change, characterized by a shrinking middle of the distribution and a growing top and bottom, with potentially important and unique social consequences. Building on relative distribution methods and drawing from the literature on job polarization, the authors develop an approach for analyzing economic polarization at the individual level. The method has three useful features. First, it offers intuitive and flexible measurement of economic polarization both between and within categories. Second, it helps disentangle two potential sources of economic polarization: compositional change, which involves changes to the allocation of workers across categories, and relative economic status change, which involves changes to the allocation of economic rewards between individuals. Third, it enables researchers to uncover and examine potential heterogeneity in economic polarization, for example, across occupations, geographic units, demographic and educational groups, and firms. The authors demonstrate the utility of this approach through two empirical applications: (1) an analysis of trends in wage polarization between and within occupations and (2) an examination of geographic variation in income polarization.
      Citation: Sociological Methodology
      PubDate: 2024-07-25T10:36:10Z
      DOI: 10.1177/00811750241260731
       
  • Contextual Embeddings in Sociological Research: Expanding the Analysis of
           Sentiment and Social Dynamics

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      Authors: Moeen Mostafavi, Michael D. Porter, Dawn T. Robinson
      Abstract: Sociological Methodology, Ahead of Print.
      The authors introduce BERTNN (Bidirectional Encoder Representations from Transformers Neural Network), a novel methodology designed to expand affective lexicons, a critical component in sociological research. BERTNN estimates the affective meanings and their distribution for new concepts, bypassing the need for extensive surveys by leveraging their contextual usage in language. The cornerstone of BERTNN is the use of nuanced word embeddings from Bidirectional Encoder Representations from Transformers. BERTNN uniquely encodes words within the framework of synthesized social event sentences, preserving their meaning across actor-behavior-object positions. The model is fine-tuned on the basis of the implied sentiment changes, providing a more refined estimation of affective meanings. BERTNN outperforms previous approaches, setting a new standard in deriving multidimensional affective meanings for novel concepts. It efficiently replicates sentiment ratings that traditionally require extensive survey hours, demonstrating the power of automated modeling in sociological research. The expanded affective lexicons that can be produced with BERTNN cater to shifting cultural meanings and diverse subgroups, demonstrating the potential of computational linguistics to enrich the measurement tools in sociological research. This article underscores the novelty and significance of BERTNN in the broader context of sociological methodology.
      Citation: Sociological Methodology
      PubDate: 2024-07-25T10:32:52Z
      DOI: 10.1177/00811750241260729
       
  • Question-Order Effect in the Study of Satisfaction with Democracy: Lessons
           from Three Split-Ballot Experiments

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      Authors: Zsófia Papp, Pál Susánszky, Andrea Szabó
      Abstract: Sociological Methodology, Ahead of Print.
      This study examines question-order effects in measuring satisfaction with democracy (SWD). Particularly, the authors are interested in whether the relative position of the question regarding satisfaction with the state of the economy (SWE) in the questionnaire affects responses to the SWD item. The authors conducted three independent split-ballot experiments in Hungary between March 2021 and May 2022. They report a significant and substantial negative priming effect that possibly leads to a systematic underestimation of SWD. Importantly, the authors find no question-order effect in the measurement of SWE. The analysis further reveals a contrast effect: when the SWD question is primed, the difference between SWE and SWD means increases. The authors’ final recommendation is that researchers either put the SWD question before the SWE item to avoid question-order bias or randomize question order. These findings should assist future data collection efforts (comparative or single-country studies) in developing and integrating a battery of satisfaction items into questionnaires and help users assess data quality.
      Citation: Sociological Methodology
      PubDate: 2024-05-28T08:54:21Z
      DOI: 10.1177/00811750241254363
       
  • Comparing the Robustness of Simple Network Scale-Up Method Estimators

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      Authors: Jessica P. Kunke, Ian Laga, Xiaoyue Niu, Tyler H. McCormick
      Abstract: Sociological Methodology, Ahead of Print.
      The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents’ degrees and estimating the prevalence of the hard-to-reach population of interest using respondents’ estimated degrees and the number of people they report knowing in the hard-to-reach group. Each of these two steps involves taking either an average of ratios or a ratio of averages. Using the ratio of averages for each step has so far been the most common approach. However, the authors present theoretical arguments that using the average of ratios at the second, prevalence-estimation step often has lower mean squared error when the random mixing assumption is violated, which seems likely in practice; this estimator was proposed early in NSUM development but has largely been unexplored and unused. Simulation results using an example network data set also support these findings. On the basis of this theoretical and empirical evidence, the authors suggest that future surveys that use a simple estimator may want to use this mixed estimator, and estimation methods based on this estimator may produce new improvements.
      Citation: Sociological Methodology
      PubDate: 2024-04-15T06:39:44Z
      DOI: 10.1177/00811750241242791
       
  • Multivariate Multinomial Logit Models with Associations among Dependent
           Variables

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      Authors: Kazuo Yamaguchi, Jesse Zhou
      Abstract: Sociological Methodology, Ahead of Print.
      The authors introduce a new group of multinomial logit models with special contrasts to identify covariate effects on multiple categorical dependent variables that are strongly associated with each other. The authors first develop the method for a case with two dependent variables and then extend the method to a case with three dependent variables. The model can account for both nominal and ordinal scales of categorical dependent variables. The authors formulate the covariate effects to represent unique effects on each dependent variable so that they become independent across different dependent variables. The application focuses on the multiplicity of occupational attainments by analyzing how gender, race, educational attainment, and parental occupation characteristics affect three distinct but nonindependent dimensions of occupations: socioeconomic status, social skill level, and math and science skill levels.
      Citation: Sociological Methodology
      PubDate: 2024-04-12T06:23:31Z
      DOI: 10.1177/00811750241239049
       
  • Polygenic Indices (aka Polygenic Scores) in Social Science: A Guide for
           Interpretation and Evaluation

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      Authors: Callie H. Burt
      Abstract: Sociological Methodology, Ahead of Print.
      Polygenic indices (PGI)—the new recommended label for polygenic scores in social science applications—are genetic summary scales often used to represent an individual’s liability for a disease, trait, or behavior on the basis of the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science data sets have facilitated increased uptake of PGIs in social science research, a trend that will likely continue. Yet most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, I provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. I summarize recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. I conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.
      Citation: Sociological Methodology
      PubDate: 2024-03-21T10:42:18Z
      DOI: 10.1177/00811750241236482
       
  • Abductive Cross-Case Comparison in Qualitative Research: Methodological
           Lessons from the Teamwork Study of Professional Change

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      Authors: Inge Kryger Pedersen, Anders Blok
      Abstract: Sociological Methodology, Ahead of Print.
      The authors argue that hitherto separate methodological conversations about abduction and comparison can be fruitfully brought together to generate novel, well-founded insights and retheorize an object of study in multiple-case qualitative inquiry. The authors call this abductive cross-case comparison and illustrate it by way of a collective study of how professional boundary work is changing under transnational conditions. In this study, the authors faced a common challenge in qualitative-comparative research: what to do when initial observations generate “surprises” that seem to confound the theoretical frameworks undergirding the comparison' To discuss how abductive inferences supported the authors’ response to this challenge, they explicate the acts of discovery and (re)conceptualization involved through various steps in a team-based research process. Building on the existing qualitative comparison literature, the authors suggest that such procedures fill a methodological gap and may hold great promise for overcoming obstacles in designing and implementing comparative research. Overall, the authors explicate and illustrate the method of abductive cross-case comparison, including their work as a research team. The aim of this article is thus to help sociologists implement better qualitative research that leverages a fuller potential of comparative designs to push beyond established knowledge and frameworks.
      Citation: Sociological Methodology
      PubDate: 2024-02-13T06:36:37Z
      DOI: 10.1177/00811750241228597
       
  • Micro-Macro Mediation Analysis in Social Networks

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      Authors: Scott W. Duxbury
      Abstract: Sociological Methodology, Ahead of Print.
      Mediation analysis is increasingly used in the social sciences. Extension to social network data, however, has proved difficult because statistical network models are formulated at a lower level of analysis (the dyad) than many outcomes of interest. This study introduces a general approach for micro-macro mediation analysis in social networks. The author defines the average mediated micro effect (AMME) as the indirect effect of a network selection process on an individual, group, or organizational outcome through its effect on an intervening network variable. The author shows that the AMME can be nonparametrically identified using a wide range of common statistical network and regression modeling strategies under the assumption of conditional independence among multiple mediators. Nonparametric and parametric algorithms are introduced to generically estimate the AMME in a multitude of research designs. The author illustrates the utility of the method with an applied example using cross-sectional National Longitudinal Study of Adolescent to Adult Health data to examine the friendship selection mechanisms that indirectly shape adolescent school performance through their effect on network structure.
      Citation: Sociological Methodology
      PubDate: 2024-02-05T11:02:32Z
      DOI: 10.1177/00811750231220950
       
  • Incorporating Machine Learning into Sociological Model-Building

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      Authors: Mark D. Verhagen
      Abstract: Sociological Methodology, Ahead of Print.
      Quantitative sociologists frequently use simple linear functional forms to estimate associations among variables. However, there is little guidance on whether such simple functional forms correctly reflect the underlying data-generating process. Incorrect model specification can lead to misspecification bias, and a lack of scrutiny of functional forms fosters interference of researcher degrees of freedom in sociological work. In this article, I propose a framework that uses flexible machine learning (ML) methods to provide an indication of the fit potential in a dataset containing the exact same covariates as a researcher’s hypothesized model. When this ML-based fit potential strongly outperforms the researcher’s self-hypothesized functional form, it implies a lack of complexity in the latter. Advances in the field of explainable AI, like the increasingly popular Shapley values, can be used to generate understanding into the ML model such that the researcher’s original functional form can be improved accordingly. The proposed framework aims to use ML beyond solely predictive questions, helping sociologists exploit the potential of ML to identify intricate patterns in data to specify better-fitting, interpretable models. I illustrate the proposed framework using a simulation and real-world examples.
      Citation: Sociological Methodology
      PubDate: 2024-01-13T11:01:20Z
      DOI: 10.1177/00811750231217734
       
  • Micro Effects on Macro Structure in Social Networks

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      Authors: Scott W. Duxbury
      Abstract: Sociological Methodology, Ahead of Print.
      How do individuals’ network selection decisions create unique network structures' Despite broad sociological interest in the micro-level social interactions that create macro-level network structure, few methods are available to statistically evaluate micro-macro relationships in social networks. This study introduces a general methodological framework for testing the effect of (micro) network selection processes, such as homophily, reciprocity, or preferential attachment, on unique (macro) network structures, such as segregation, clustering, or brokerage. The approach uses estimates from a statistical network model to decompose the contributions of each parameter to a node, subgraph, or global network statistic specified by the researcher. A flexible parametric algorithm is introduced to estimate variances, confidence intervals, and p values. Prior micro-macro network methods can be regarded as special cases of the general framework. Extensions to hypothetical network interventions, joint parameter tests, and longitudinal and multilevel network data are discussed. An example is provided analyzing the micro foundations of political segregation in a crime policy collaboration network.
      Citation: Sociological Methodology
      PubDate: 2023-11-08T12:29:57Z
      DOI: 10.1177/00811750231209040
       
  • Marginal-Preserving Imputation of Three-Way Array Data in Nested
           Structures, with Application to Small Areal Units

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      Authors: Loring J. Thomas, Peng Huang, Xiaoshuang Iris Luo, John R. Hipp, Carter T. Butts
      Abstract: Sociological Methodology, Ahead of Print.
      Geospatial population data are typically organized into nested hierarchies of areal units, in which each unit is a union of units at the next lower level. There is increasing interest in analyses at fine geographic detail, but these lowest rungs of the areal unit hierarchy are often incompletely tabulated because of cost, privacy, or other considerations. Here, the authors introduce a novel algorithm to impute crosstabs of up to three dimensions (e.g., race, ethnicity, and gender) from marginal data combined with data at higher levels of aggregation. This method exactly preserves the observed fine-grained marginals, while approximating higher-order correlations observed in more complete higher level data. The authors show how this approach can be used with U.S. census data via a case study involving differences in exposure to crime across demographic groups, showing that the imputation process introduces very little error into downstream analysis, while depicting social process at the more fine-grained level.
      Citation: Sociological Methodology
      PubDate: 2023-11-08T12:00:16Z
      DOI: 10.1177/00811750231203218
       
  • Networked Participants, Networked Meanings: Using Networks to Visualize
           Ethnographic Data

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      Authors: Kenneth R. Hanson, Nicholas Theis
      Abstract: Sociological Methodology, Ahead of Print.
      Researchers can use data visualization techniques to explore, analyze, and present data in new ways. Although quantitative data are visualized most often, recent innovations have brought attention to the potential benefits of visualizing qualitative data. In this article, the authors demonstrate one way researchers can use networks to analyze and present ethnographic interview data. The authors suggest that because many respondents know one another in ethnographic research, networks are a useful tool for analyzing the implications of respondents’ familiarity with one another. Moreover, respondents often share familiar cultural references that can be visualized. The authors show how visualizing respondents’ ties in conjunction with their shared cultural references sheds light on the different systems of meaning that respondents within a field site use to make sense of the social phenomena under investigation.
      Citation: Sociological Methodology
      PubDate: 2023-09-07T11:54:33Z
      DOI: 10.1177/00811750231195338
       
  • Trend Analysis with Pooled Data from Different Survey Series: The Latent
           Attitude Method

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      Authors: Donghui Wang, Yu Xie, Junming Huang
      Abstract: Sociological Methodology, Ahead of Print.
      The use of pooled data from different repeated survey series to study long-term trends is handicapped by a measurement difficulty: different survey series often use different scales to measure the same attitude and thus generate scale-incomparable data. In this article, the authors propose the latent attitude method (LAM) to address this scale-incomparability problem, on the basis of the assumption that attitudes measured by ordinal categories reflect a latent attitude with cut points. The method extends the latent variable method in the case of a single survey series to the case of multiple survey series and leverages overlapping years for identification. The authors first assess the validity of the method with simulated data. The results show that the method yields accurate estimates of mean attitudes and cut point values. The authors then apply the method to an empirical study of Americans’ attitudes toward China from 1974 to 2019.
      Citation: Sociological Methodology
      PubDate: 2023-09-05T09:53:25Z
      DOI: 10.1177/00811750231193641
       
  • Choosing an Optimal Method for Causal Decomposition Analysis with
           Continuous Outcomes: A Review and Simulation Study

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      Authors: Soojin Park, Suyeon Kang, Chioun Lee
      Abstract: Sociological Methodology, Ahead of Print.
      Causal decomposition analysis is among the rapidly growing number of tools for identifying factors (“mediators”) that contribute to disparities in outcomes between social groups. An example of such mediators is college completion, which explains later health disparities between Black women and White men. The goal is to quantify how much a disparity would be reduced (or remain) if we hypothetically intervened to set the mediator distribution equal across social groups. Despite increasing interest in estimating disparity reduction and the disparity that remains, various estimation procedures are not straightforward, and researchers have scant guidance for choosing an optimal method. In this article, the authors evaluate the performance in terms of bias, variance, and coverage of three approaches that use different modeling strategies: (1) regression-based methods that impose restrictive modeling assumptions (e.g., linearity) and (2) weighting-based and (3) imputation-based methods that rely on the observed distribution of variables. The authors find a trade-off between the modeling assumptions required in the method and its performance. In terms of performance, regression-based methods operate best as long as the restrictive assumption of linearity is met. Methods relying on mediator models without imposing any modeling assumptions are sensitive to the ratio of the group-mediator association to the mediator-outcome association. These results highlight the importance of selecting an appropriate estimation procedure considering the data at hand.
      Citation: Sociological Methodology
      PubDate: 2023-07-17T11:24:24Z
      DOI: 10.1177/00811750231183711
       
  • A Model of Dynamic Flows: Explaining Turkey’s Interprovincial
           Migration

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      Authors: Ozan Aksoy, Sinan Yıldırım
      Abstract: Sociological Methodology, Ahead of Print.
      The flow of resources across nodes over time (e.g., migration, financial transfers, peer-to-peer interactions) is a common phenomenon in sociology. Standard statistical methods are inadequate to model such interdependent flows. We propose a hierarchical Dirichlet-multinomial regression model and a Bayesian estimation method. We apply the model to analyze 25,632,876 migration instances that took place between Turkey’s 81 provinces from 2009 to 2018. We then discuss the methodological and substantive implications of our results. Methodologically, we demonstrate the predictive advantage of our model compared to its most common alternative in migration research, the gravity model. We also discuss our model in the context of other approaches, mostly developed in the social networks literature. Substantively, we find that population, economic prosperity, the spatial and political distance between the origin and destination, the strength of the AKP (Justice and Development Party) in a province, and the network characteristics of the provinces are important predictors of migration, whereas the proportion of ethnic minority Kurds in a province has no positive association with in- and out-migration.
      Citation: Sociological Methodology
      PubDate: 2023-07-11T10:29:44Z
      DOI: 10.1177/00811750231184460
       
  • From Sequences to Variables: Rethinking the Relationship between Sequences
           and Outcomes

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      Authors: Satu Helske, Jouni Helske, Guilherme K. Chihaya
      Abstract: Sociological Methodology, Ahead of Print.
      Sequence analysis is increasingly used in the social sciences for the holistic analysis of life-course and other longitudinal data. The usual approach is to construct sequences, calculate dissimilarities, group similar sequences with cluster analysis, and use cluster membership as a dependent or independent variable in a regression model. This approach may be problematic, as cluster memberships are assumed to be fixed known characteristics of the subjects in subsequent analyses. Furthermore, it is often more reasonable to assume that individual sequences are mixtures of multiple ideal types rather than equal members of some group. Failing to account for uncertain and mixed memberships may lead to wrong conclusions about the nature of the studied relationships. In this article, the authors bring forward and discuss the problems of the “traditional” use of sequence analysis clusters as variables and compare four approaches for creating explanatory variables from sequence dissimilarities using different types of data. The authors conduct simulation and empirical studies, demonstrating the importance of considering how sequences and outcomes are related and the need to adjust analyses accordingly. In many typical social science applications, the traditional approach is prone to result in wrong conclusions, and similarity-based approaches such as representativeness should be preferred.
      Citation: Sociological Methodology
      PubDate: 2023-06-15T09:19:10Z
      DOI: 10.1177/00811750231177026
       
 
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  First | 1 2 3        [Sort by number of followers]   [Restore default list]

  Subjects -> SOCIOLOGY (Total: 553 journals)
Showing 401 - 382 of 382 Journals sorted alphabetically
Tla-Melaua : Revista de Ciencias Sociales     Open Access  
Tracés     Open Access  
Trajecta : Religion, Culture and Society in the Low Countries     Open Access  
Transatlantica     Open Access   (Followers: 2)
Transmotion     Open Access   (Followers: 14)
Transposition : Musique et sciences sociales     Open Access   (Followers: 1)
Travail et Emploi     Open Access   (Followers: 5)
TRIM. Tordesillas : Revista de investigación multidisciplinar     Open Access  
Universidad, Escuela y Sociedad     Open Access   (Followers: 1)
Unoesc & Ciência - ACHS     Open Access  
Urban Research & Practice     Hybrid Journal   (Followers: 23)
Valuation Studies     Open Access   (Followers: 2)
Variations : Revue Internationale de Théorie Critique     Open Access   (Followers: 1)
Visitor Studies     Hybrid Journal   (Followers: 4)
Vlast' (The Authority)     Open Access  
Work, Aging and Retirement     Open Access   (Followers: 4)
World Future Review     Hybrid Journal   (Followers: 1)
Zeitschrift für Religion, Gesellschaft und Politik     Hybrid Journal  

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