Pub Date : 2025-07-25DOI: 10.1177/00491241251345457
Lukas Olbrich, Joseph W. Sakshaug, Eric Lewandowski
Inattentive respondents pose a substantial threat to data quality in web surveys. We evaluate methods for preventing and detecting inattentive respondents. First, we test the effect of asking respondents to commit to providing high-quality responses at the beginning of the survey on various data quality measures. Second, we compare the proportion of flagged respondents for two versions of an attention check item instructing them to select a specific response versus leaving the item blank. Third, we propose a timestamp-based cluster analysis approach that identifies clusters of respondents who exhibit different speeding behaviors. Our findings show that the commitment pledge had no effect on the data quality measures. Instructing respondents to leave the item blank significantly increased the rate of flagged respondents (by 16.8 percentage points). The timestamp-based clustering approach efficiently identified clusters of likely inattentive respondents. Lastly, we show that inattentive respondents can have substantial impacts on substantive analyses.
{"title":"Evaluating Methods to Prevent and Detect Inattentive Respondents in Web Surveys","authors":"Lukas Olbrich, Joseph W. Sakshaug, Eric Lewandowski","doi":"10.1177/00491241251345457","DOIUrl":"https://doi.org/10.1177/00491241251345457","url":null,"abstract":"Inattentive respondents pose a substantial threat to data quality in web surveys. We evaluate methods for preventing and detecting inattentive respondents. First, we test the effect of asking respondents to commit to providing high-quality responses at the beginning of the survey on various data quality measures. Second, we compare the proportion of flagged respondents for two versions of an attention check item instructing them to select a specific response versus leaving the item blank. Third, we propose a timestamp-based cluster analysis approach that identifies clusters of respondents who exhibit different speeding behaviors. Our findings show that the commitment pledge had no effect on the data quality measures. Instructing respondents to leave the item blank significantly increased the rate of flagged respondents (by 16.8 percentage points). The timestamp-based clustering approach efficiently identified clusters of likely inattentive respondents. Lastly, we show that inattentive respondents can have substantial impacts on substantive analyses.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"13 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144737175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-09DOI: 10.1177/00491241251349148
Lawrence E. Blume, Neil A. Cholli, Steven N. Durlauf, Aleksandra Lukina
This article proposes some new measures of intergenerational persistence based on the idea of characterizing the memory of origin in the stochastic process that links the socioeconomic classes of parents and children. We introduce “memory curves” for all future generations given any initial condition of class for a family dynasty, which reveal how initial conditions interact with the transition process between parents and children to create mobility and persistence. We also propose ways to aggregate information across different classes to produce overall characterizations of mobility in the population. To illustrate our measures, we estimate occupational “memory curves” using U.S. survey data. Our findings show that, on average, the memory of initial conditions dissipates largely within three generations, though there is meaningful heterogeneity in mobility rates across dynasties originating from different occupational classes.
{"title":"Immobility as Memory: Some New Approaches to Characterizing Intergenerational Persistence via Markov Chains","authors":"Lawrence E. Blume, Neil A. Cholli, Steven N. Durlauf, Aleksandra Lukina","doi":"10.1177/00491241251349148","DOIUrl":"https://doi.org/10.1177/00491241251349148","url":null,"abstract":"This article proposes some new measures of intergenerational persistence based on the idea of characterizing the memory of origin in the stochastic process that links the socioeconomic classes of parents and children. We introduce “memory curves” for all future generations given any initial condition of class for a family dynasty, which reveal how initial conditions interact with the transition process between parents and children to create mobility and persistence. We also propose ways to aggregate information across different classes to produce overall characterizations of mobility in the population. To illustrate our measures, we estimate occupational “memory curves” using U.S. survey data. Our findings show that, on average, the memory of initial conditions dissipates largely within three generations, though there is meaningful heterogeneity in mobility rates across dynasties originating from different occupational classes.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"82 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-09DOI: 10.1177/00491241251344289
Jonathan Burton, Mick P. Couper, Thomas F. Crossley, Annette Jäckle, Sandra Walzenbach
Linkages between surveys and administrative data provide an important opportunity for social and health research, but such linkages often require the informed consent of respondents. We use experimental data collection across five different samples to study how consent decisions are made. More reflective decision processes are associated with higher rates of consent, greater comprehension of the proposed data linkage, and greater confidence in the decision, but only about a third of respondents report using a reflective decision process. This suggests that the provision of additional information is unlikely to lead to significant improvements in informed consent.
{"title":"How Do Survey Respondents Decide Whether to Consent to Data Linkage?","authors":"Jonathan Burton, Mick P. Couper, Thomas F. Crossley, Annette Jäckle, Sandra Walzenbach","doi":"10.1177/00491241251344289","DOIUrl":"https://doi.org/10.1177/00491241251344289","url":null,"abstract":"Linkages between surveys and administrative data provide an important opportunity for social and health research, but such linkages often require the informed consent of respondents. We use experimental data collection across five different samples to study how consent decisions are made. More reflective decision processes are associated with higher rates of consent, greater comprehension of the proposed data linkage, and greater confidence in the decision, but only about a third of respondents report using a reflective decision process. This suggests that the provision of additional information is unlikely to lead to significant improvements in informed consent.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"21 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144586487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-02DOI: 10.1177/00491241251355640
Yoosoon Chang, Steven N. Durlauf, Fabian T. Pfeffer, Xi Song
This special issue of Sociological Methods & Research presents a collection of papers that develop a range of new statistical approaches and empirical insights on intergenerational mobility. The papers in the special issue involve four broad themes: the development of new statistics to characterize mobility, the exploration of methods to establish causal explanations, the enrichment of statistical models to better characterize heterogeneity in mobility across families, and the development and application of ways to employ machine learning tools to enrich mobility analysis. These papers demonstrate the excitement of the methodological frontier in mobility research.
{"title":"Methodological Frontiers in Intergenerational Mobility Research","authors":"Yoosoon Chang, Steven N. Durlauf, Fabian T. Pfeffer, Xi Song","doi":"10.1177/00491241251355640","DOIUrl":"https://doi.org/10.1177/00491241251355640","url":null,"abstract":"This special issue of Sociological Methods & Research presents a collection of papers that develop a range of new statistical approaches and empirical insights on intergenerational mobility. The papers in the special issue involve four broad themes: the development of new statistics to characterize mobility, the exploration of methods to establish causal explanations, the enrichment of statistical models to better characterize heterogeneity in mobility across families, and the development and application of ways to employ machine learning tools to enrich mobility analysis. These papers demonstrate the excitement of the methodological frontier in mobility research.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"20 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-25DOI: 10.1177/00491241251336794
Oscar Stuhler, Cat Dang Ton, Etienne Ollion
Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural Language Processing, but leveraging the affordances of this paradigm has thus far required familiarity with specialized models. GenAI changes this by allowing researchers to define their own IE tasks and execute them via targeted prompts. This article explores the potential of open-source large language models for IE by extracting and encoding biographical information (e.g., age, occupation, origin) from a corpus of newspaper obituaries. As we proceed, we discuss how sociologists can develop and evaluate prompt architectures for such tasks, turning codebooks into “promptbooks.” We also evaluate models of different sizes and prompting techniques. Our analysis showcases the potential of GenAI as a flexible and accessible tool for IE while also underscoring risks like non-random error patterns that can bias downstream analyses.
{"title":"From Codebooks to Promptbooks: Extracting Information from Text with Generative Large Language Models","authors":"Oscar Stuhler, Cat Dang Ton, Etienne Ollion","doi":"10.1177/00491241251336794","DOIUrl":"https://doi.org/10.1177/00491241251336794","url":null,"abstract":"Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural Language Processing, but leveraging the affordances of this paradigm has thus far required familiarity with specialized models. GenAI changes this by allowing researchers to define their own IE tasks and execute them via targeted prompts. This article explores the potential of open-source large language models for IE by extracting and encoding biographical information (e.g., age, occupation, origin) from a corpus of newspaper obituaries. As we proceed, we discuss how sociologists can develop and evaluate prompt architectures for such tasks, turning codebooks into “promptbooks.” We also evaluate models of different sizes and prompting techniques. Our analysis showcases the potential of GenAI as a flexible and accessible tool for IE while also underscoring risks like non-random error patterns that can bias downstream analyses.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"20 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144479192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-20DOI: 10.1177/00491241251341196
Martin Nybom, Jan Stuhler
Using complete-count register data spanning three generations, we document spatial patterns in inter- and multi-generational mobility in Sweden. Across municipalities, grandfather–child correlations in education or earnings tend to be larger than the square of the parent–child correlations, suggesting that the latter understate status transmission in the long run. Yet, conventional parent–child correlations capture regional differences in long-run transmission and therefore remain useful for comparative purposes. We further find that the within-country association between mobility and income inequality (the “Great Gatsby Curve”) is at least as strong in the multi- as in the inter-generational case. Interpreting those patterns through the lens of a latent factor model, we find that regional differences in mobility primarily reflect variation in the transmission of latent advantages, rather than in how those advantages translate into observed outcomes.
{"title":"Geographic Variation in Multigenerational Mobility","authors":"Martin Nybom, Jan Stuhler","doi":"10.1177/00491241251341196","DOIUrl":"https://doi.org/10.1177/00491241251341196","url":null,"abstract":"Using complete-count register data spanning three generations, we document spatial patterns in inter- and multi-generational mobility in Sweden. Across municipalities, grandfather–child correlations in education or earnings tend to be larger than the square of the parent–child correlations, suggesting that the latter understate status transmission in the long run. Yet, conventional parent–child correlations capture regional <jats:italic>differences</jats:italic> in long-run transmission and therefore remain useful for comparative purposes. We further find that the within-country association between mobility and income inequality (the “Great Gatsby Curve”) is at least as strong in the multi- as in the inter-generational case. Interpreting those patterns through the lens of a latent factor model, we find that regional differences in mobility primarily reflect variation in the transmission of latent advantages, rather than in how those advantages translate into observed outcomes.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"175 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144328662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-20DOI: 10.1177/00491241251347982
Deirdre Bloome
Researchers concerned about intergenerational inequalities study absolute and relative mobility (e.g., whether people’s adult incomes exceed their parents’ incomes in dollars or ranks ). Absolute and relative mobility are connected, by definition. Yet, they are not equivalent. Indeed, they often diverge. To illuminate why, when, and for whom such divergence occurs—and why, when, and for whom convergence is possible—this article provides two frameworks for connecting absolute and relative mobility. One framework is formal and one is typological. Both frameworks center micro-level socioeconomic experiences across generations. Illustrative analyses employ these frameworks using National Longitudinal Survey of Youth data. Results suggest that divergent experiences, like upward absolute mobility despite downward relative mobility, may be more common among more advantaged social groups. Future researchers could use the two frameworks introduced here to further advance our understanding of how intergenerational inequalities evolve differently in absolute and relative terms.
{"title":"Absolute and Relative Mobility: Two Frameworks for Connecting Intergenerational Mobility in Absolute and Relative Terms","authors":"Deirdre Bloome","doi":"10.1177/00491241251347982","DOIUrl":"https://doi.org/10.1177/00491241251347982","url":null,"abstract":"Researchers concerned about intergenerational inequalities study <jats:italic>absolute</jats:italic> and <jats:italic>relative</jats:italic> mobility (e.g., whether people’s adult incomes exceed their parents’ incomes in <jats:italic>dollars</jats:italic> or <jats:italic>ranks</jats:italic> ). Absolute and relative mobility are connected, by definition. Yet, they are not equivalent. Indeed, they often diverge. To illuminate why, when, and for whom such divergence occurs—and why, when, and for whom convergence is possible—this article provides two frameworks for connecting absolute and relative mobility. One framework is formal and one is typological. Both frameworks center micro-level socioeconomic experiences across generations. Illustrative analyses employ these frameworks using National Longitudinal Survey of Youth data. Results suggest that divergent experiences, like upward absolute mobility despite downward relative mobility, may be more common among more advantaged social groups. Future researchers could use the two frameworks introduced here to further advance our understanding of how intergenerational inequalities evolve <jats:italic>differently</jats:italic> in absolute and relative terms.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"7 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144328660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-19DOI: 10.1177/00491241251347983
Xi Song, Xiang Zhou
Social mobility scholars have long been interested in estimating the effect of intergenerational mobility, typically measured by differences in the socioeconomic status between parents and offspring, on later-life outcomes of offspring. In a 2022 article “Heterogeneous Effects of Intergenerational Social Mobility: An Improved Method and New Evidence,” Luo proposes a new approach called the mobility contrast model (MCM) to define and estimate mobility effects. We argue that the MCM is inherently flawed due to its reliance on the coding scheme used for the categorical variables of social origin and destination. Specifically, when different coding schemes are applied, the estimands defined in the MCM bear distinct meanings, involve different but equally arbitrary constraints, and sometimes yield contradictory results. Moreover, regardless of the coding scheme, these estimands do not adequately capture the sociological concept of a mobility effect. To illustrate this, we reanalyze the Occupational Changes in a Generation Study data used in Luo’s study, highlighting the inconsistency of results when dummy coding versus effect coding schemes are used.
{"title":"Is There a Mobility Effect? On Methodological Issues in the Mobility Contrast Model","authors":"Xi Song, Xiang Zhou","doi":"10.1177/00491241251347983","DOIUrl":"https://doi.org/10.1177/00491241251347983","url":null,"abstract":"Social mobility scholars have long been interested in estimating the effect of intergenerational mobility, typically measured by differences in the socioeconomic status between parents and offspring, on later-life outcomes of offspring. In a 2022 article “Heterogeneous Effects of Intergenerational Social Mobility: An Improved Method and New Evidence,” Luo proposes a new approach called the mobility contrast model (MCM) to define and estimate mobility effects. We argue that the MCM is inherently flawed due to its reliance on the coding scheme used for the categorical variables of social origin and destination. Specifically, when different coding schemes are applied, the estimands defined in the MCM bear distinct meanings, involve different but equally arbitrary constraints, and sometimes yield contradictory results. Moreover, regardless of the coding scheme, these estimands do not adequately capture the sociological concept of a mobility effect. To illustrate this, we reanalyze the Occupational Changes in a Generation Study data used in Luo’s study, highlighting the inconsistency of results when dummy coding versus effect coding schemes are used.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"19 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144328666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-19DOI: 10.1177/00491241251347984
Haowen Zheng, Siwei Cheng
How well can individuals’ parental background and previous life experiences predict their mid-life socioeconomic status (SES) attainment? This question is central to stratification research, as a strong power of earlier experiences in predicting later-life outcomes signals substantial intra- or intergenerational status persistence, or put simply, social rigidity. Running machine learning models on panel data to predict outcomes that include hourly wage, total income, family income, and occupational status, we find that a large number (around 4,000) of predictors commonly used in the stratification literature improves the prediction of one’s life chances in middle to late adulthood by about 10 percent to 50 percent, compared with a null model that uses a simple mean of the outcome variable. The level of predictability depends on the specific outcome being analyzed, with labor market indicators like wages and occupational prestige being more predictable than broader socioeconomic measures such as overall personal and family income. Grouping a comprehensive list of predictors into four unique sets that cover family background, childhood and adolescence development, early labor market experiences, and early adulthood family formation, we find that including income, employment status, and occupational characteristics at early career significantly improves models’ prediction accuracy for mid-life SES attainment. We also illustrate the application of the predictive models to examine heterogeneity in predictability by race and gender and identify important variables through this data-driven exercise.
{"title":"Social Rigidity Across and Within Generations: A Predictive Approach","authors":"Haowen Zheng, Siwei Cheng","doi":"10.1177/00491241251347984","DOIUrl":"https://doi.org/10.1177/00491241251347984","url":null,"abstract":"How well can individuals’ parental background and previous life experiences predict their mid-life socioeconomic status (SES) attainment? This question is central to stratification research, as a strong power of earlier experiences in predicting later-life outcomes signals substantial intra- or intergenerational status persistence, or put simply, social rigidity. Running machine learning models on panel data to predict outcomes that include hourly wage, total income, family income, and occupational status, we find that a large number (around 4,000) of predictors commonly used in the stratification literature improves the prediction of one’s life chances in middle to late adulthood by about 10 percent to 50 percent, compared with a null model that uses a simple mean of the outcome variable. The level of predictability depends on the specific outcome being analyzed, with labor market indicators like wages and occupational prestige being more predictable than broader socioeconomic measures such as overall personal and family income. Grouping a comprehensive list of predictors into four unique sets that cover family background, childhood and adolescence development, early labor market experiences, and early adulthood family formation, we find that including income, employment status, and occupational characteristics at early career significantly improves models’ prediction accuracy for mid-life SES attainment. We also illustrate the application of the predictive models to examine heterogeneity in predictability by race and gender and identify important variables through this data-driven exercise.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"51 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144319669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-02DOI: 10.1177/00491241251337316
Austin C. Kozlowski, James Evans
Large language models (LLMs), through their exposure to massive collections of online text, learn to reproduce the perspectives and linguistic styles of diverse social and cultural groups. This capability suggests a powerful social scientific application—the simulation of empirically realistic, culturally situated human subjects. Synthesizing recent research in artificial intelligence and computational social science, we outline a methodological foundation for simulating human subjects and their social interactions. We then identify six characteristics of current models that are likely to impair the realistic simulation of human subjects: bias, uniformity, atemporality, disembodiment, linguistic cultures, and alien intelligence. For each of these areas, we discuss promising approaches for overcoming their associated shortcomings. Given the rate of change of these models, we advocate for an ongoing methodological program for the simulation of human subjects that keeps pace with rapid technical progress, and caution that validation against human subjects data remains essential to ensure simulation accuracy.
{"title":"Simulating Subjects: The Promise and Peril of Artificial Intelligence Stand-Ins for Social Agents and Interactions","authors":"Austin C. Kozlowski, James Evans","doi":"10.1177/00491241251337316","DOIUrl":"https://doi.org/10.1177/00491241251337316","url":null,"abstract":"Large language models (LLMs), through their exposure to massive collections of online text, learn to reproduce the perspectives and linguistic styles of diverse social and cultural groups. This capability suggests a powerful social scientific application—the simulation of empirically realistic, culturally situated human subjects. Synthesizing recent research in artificial intelligence and computational social science, we outline a methodological foundation for simulating human subjects and their social interactions. We then identify six characteristics of current models that are likely to impair the realistic simulation of human subjects: bias, uniformity, atemporality, disembodiment, linguistic cultures, and alien intelligence. For each of these areas, we discuss promising approaches for overcoming their associated shortcomings. Given the rate of change of these models, we advocate for an ongoing methodological program for the simulation of human subjects that keeps pace with rapid technical progress, and caution that validation against human subjects data remains essential to ensure simulation accuracy.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"113 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：