Sociological Methods & Research最新文献_第8页

Machine Bias. How Do Generative Language Models Answer Opinion Polls? 机器的偏见。生成语言模型如何回答民意调查？

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-04-21 DOI: 10.1177/00491241251330582

Julien Boelaert, Samuel Coavoux, Étienne Ollion, Ivaylo Petev, Patrick Präg

引用次数: 0

The Insight-Inference Loop: Efficient Text Classification via Natural Language Inference and Threshold-Tuning 洞察-推理循环：基于自然语言推理和阈值调优的高效文本分类

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-04-19 DOI: 10.1177/00491241251326819

Sandrine Chausson, Marion Fourcade, David J. Harding, Björn Ross, Grégory Renard

{"title":"The Insight-Inference Loop: Efficient Text Classification via Natural Language Inference and Threshold-Tuning","authors":"Sandrine Chausson, Marion Fourcade, David J. Harding, Björn Ross, Grégory Renard","doi":"10.1177/00491241251326819","DOIUrl":"https://doi.org/10.1177/00491241251326819","url":null,"abstract":"Modern computational text classification methods have brought social scientists tantalizingly close to the goal of unlocking vast insights buried in text data—from centuries of historical documents to streams of social media posts. Yet three barriers still stand in the way: the tedious labor of manual text annotation, the technical complexity that keeps these tools out of reach for many researchers, and, perhaps most critically, the challenge of bridging the gap between sophisticated algorithms and the deep theoretical understanding social scientists have already developed about human interactions, social structures, and institutions. To counter these limitations, we propose an approach to large-scale text analysis that requires substantially less human-labeled data, and no machine learning expertise, and efficiently integrates the social scientist into critical steps in the workflow. This approach, which allows the detection of statements in text, relies on large language models pre-trained for natural language inference, and a “few-shot” threshold-tuning algorithm rooted in active learning principles. We describe and showcase our approach by analyzing tweets collected during the 2020 U.S. presidential election campaign, and benchmark it against various computational approaches across three datasets.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"1 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851025","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}

引用次数: 0

Locating Cultural Holes Brokers in Diffusion Dynamics Across Bright Symbolic Boundaries 在跨越明亮符号边界的扩散动力学中定位文化漏洞经纪人

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-03-19 DOI: 10.1177/00491241251322517

Diego F. Leal

引用次数: 0

Deep Learning With DAGs 利用 DAG 进行深度学习

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-03-12 DOI: 10.1177/00491241251319291

Sourabh Balgi, Adel Daoud, Jose M. Peña, Geoffrey T. Wodtke, Jesse Zhou

{"title":"Deep Learning With DAGs","authors":"Sourabh Balgi, Adel Daoud, Jose M. Peña, Geoffrey T. Wodtke, Jesse Zhou","doi":"10.1177/00491241251319291","DOIUrl":"https://doi.org/10.1177/00491241251319291","url":null,"abstract":"Social science theories often postulate systems of causal relationships among variables, which are commonly represented using directed acyclic graphs (DAGs). As non-parametric causal models, DAGs require no assumptions about the functional form of the hypothesized relationships. Nevertheless, to simplify empirical evaluation, researchers typically invoke such assumptions anyway, even though they are often arbitrary and do not reflect any theoretical content or prior knowledge. Moreover, functional form assumptions can engender bias, whenever they fail to accurately capture the true complexity of the system. In this article, we introduce causal-graphical normalizing flows (cGNFs), a novel approach to causal inference that leverages deep neural networks to empirically evaluate theories represented as DAGs. Unlike conventional methods, cGNFs model the full joint distribution of the data using a DAG specified by the analyst, without relying on stringent assumptions about functional form. This enables flexible, non-parametric estimation of any causal estimand identified from the DAG, including total effects, direct and indirect effects, and path-specific effects. We illustrate the method with a reanalysis of Blau and Duncan’s ( 1967 ) model of status attainment and Zhou’s ( 2019 ) model of controlled mobility. The article concludes with a discussion of current limitations and directions for future development.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"11 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143608045","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}

引用次数: 0

When to Use Counterfactuals in Causal Historiography: Methods for Semantics and Inference 在因果史学中何时使用反事实：语义学和推理方法

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-02-03 DOI: 10.1177/00491241251314039

Tay Jeong

引用次数: 0

The Integration of Bayesian Regression Analysis and Bayesian Process Tracing in Mixed-Methods Research 混合方法研究中贝叶斯回归分析与贝叶斯过程跟踪的集成

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-01-23 DOI: 10.1177/00491241241295336

Lion Behrens, Ingo Rohlfing

引用次数: 0

Improving Cross-Cultural Comparability of Measures on Gender and Age Stereotypes by Means of Piloting Methods 通过试点方法提高性别和年龄刻板印象测量的跨文化可比性

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-01-21 DOI: 10.1177/00491241241307600

Natalja Menold, Patricia Hadler, Cornelia Neuert

引用次数: 0

The Rise in Occupational Coding Mismatches and Occupational Mobility, 1991–2020 1991-2020 年职业编码错配和职业流动性的上升

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-01-16 DOI: 10.1177/00491241241303517

Andrew Taeho Kim, ChangHwan Kim

引用次数: 0

Using Google Maps to Generate Organizational Sampling Frames 使用谷歌地图生成组织采样帧

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2025-01-16 DOI: 10.1177/00491241241305095

Brad R Fulton, David P King

{"title":"Using Google Maps to Generate Organizational Sampling Frames","authors":"Brad R Fulton, David P King","doi":"10.1177/00491241241305095","DOIUrl":"https://doi.org/10.1177/00491241241305095","url":null,"abstract":"Organizational researchers use a variety of methods to obtain sampling frames. The utility of these methods, however, is constrained by access restrictions, limited coverage, prohibitive costs, and cumbersome formats. This article presents a new method for generating organizational sampling frames that is cost-effective, uses publicly available data, and can produce sampling frames for many geographic areas in the U.S. The Python-based program we developed systematically scans the Google Maps platform to identify organizations of interest and retrieve their contact information. We demonstrate the program's viability and utility by generating a sampling frame of religious congregations in the U.S. To assess Google Maps’ coverage and representativeness of such congregations, we examined two nationally representative samples of congregations and censuses of congregations in a small, medium, and large city. We found that Google Maps contains approximately 98% of those congregations––extensive coverage that ensures a high degree of representativeness. This study provides evidence that using Google Maps to generate sampling frames can improve the process for obtaining representative samples for organizational studies by reducing costs, increasing efficiency, and providing greater coverage and representativeness.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"38 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986727","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}

引用次数: 0

Examining Variation in Survey Costs Across Surveys 检查不同调查中调查成本的差异

IF 6.3 2区社会学

Sociological Methods & Research Pub Date : 2024-12-05 DOI: 10.1177/00491241241298914

Kristen Olson, John Stevenson, Nadia Assad, Lindsey Witt-Swanson, Cameron P.E. Jones, Amanda Ganshert, Jennifer Dykema

引用次数: 0