 Subjects -> SOCIOLOGY (Total: 553 journals)
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- The Effects of Open-Ended Probes on Closed Survey Questions in Web Surveys
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Authors: Patricia Hadler
Abstract: Sociological Methods & Research, Ahead of Print.
Probes are follow-ups to survey questions used to gain insights on respondents’ understanding of and responses to these questions. They are usually administered as open-ended questions, primarily in the context of questionnaire pretesting. Due to the decreased cost of data collection for open-ended questions in web surveys, researchers have argued for embedding more open-ended probes in large-scale web surveys. However, there are concerns that this may cause reactivity and impact survey data. The study presents a randomized experiment in which identical survey questions were run with and without open-ended probes. Embedding open-ended probes resulted in higher levels of survey break off, as well as increased backtracking and answer changes to previous questions. In most cases, there was no impact of open-ended probes on the cognitive processing of and response to survey questions. Implications for embedding open-ended probes into web surveys are discussed.
Citation: Sociological Methods & Research
PubDate: 2023-06-01T06:42:47Z
DOI: 10.1177/00491241231176846
- Graphical Causal Models for Survey Inference
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Authors: Julian Schuessler, Peter Selb
Abstract: Sociological Methods & Research, Ahead of Print.
Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of bias and assumptions for eliminating it in various selection scenarios. We then introduce and analyze graphical representations of multiple selection stages in the data collection process, and highlight the strong assumptions implicit in using only design weights. Furthermore, we show that the common practice of selecting adjustment variables based on correlations with sample selection and outcome variables of interest is ill-justified and that nonresponse weighting when the interest is in causal inference may come at severe costs. Finally, we identify further areas for survey methodology research that can benefit from advances in causal graph theory.
Citation: Sociological Methods & Research
PubDate: 2023-05-31T06:14:22Z
DOI: 10.1177/00491241231176851
- Linear Probability Model Revisited: Why It Works and How It Should Be
Specified-
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Authors: Myoung-jae Lee,
Goeun Lee, Jin-young Choi
Abstract: Sociological Methods & Research, Ahead of Print.
A linear model is often used to find the effect of a binary treatment [math] on a noncontinuous outcome [math] with covariates [math]. Particularly, a binary [math] gives the popular “linear probability model (LPM),” but the linear model is untenable if [math] contains a continuous regressor. This raises the question: what kind of treatment effect does the ordinary least squares estimator (OLS) to LPM estimate' This article shows that the OLS estimates a weighted average of the [math]-conditional heterogeneous effect plus a bias. Under the condition that [math] is equal to the linear projection of [math] on [math], the bias becomes zero, and the OLS estimates the “overlap-weighted average” of the [math]-conditional effect. Although the condition does not hold in general, specifying the [math]-part of the LPM such that the [math]-part predicts [math] well, not [math], minimizes the bias counter-intuitively. This article also shows how to estimate the overlap-weighted average without the condition by using the “propensity-score residual” [math]. An empirical analysis demonstrates our points.
Citation: Sociological Methods & Research
PubDate: 2023-05-30T03:48:00Z
DOI: 10.1177/00491241231176850
- Exploring and Correcting the Bias in the Estimation of the Gini Measure of
Inequality-
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Authors: Juan F. Muñoz, Pablo J. Moya-Fernández, Encarnación Álvarez-Verdejo
Abstract: Sociological Methods & Research, Ahead of Print.
The Gini index is probably the most commonly used indicator to measure inequality. For continuous distributions, the Gini index can be computed using several equivalent formulations. However, this is not the case with discrete distributions, where controversy remains regarding the expression to be used to estimate the Gini index. We attempt to bring a better understanding of the underlying problem by regrouping and classifying the most common estimators of the Gini index proposed in both infinite and finite populations, and focusing on the biases. We use Monte Carlo simulation studies to analyse the bias of the various estimators under a wide range of scenarios. Extremely large biases are observed in heavy-tailed distributions with high Gini indices, and bias corrections are recommended in this situation. We propose the use of some (new and traditional) bootstrap-based and jackknife-based strategies to mitigate this bias problem. Results are based on continuous distributions often used in the modelling of income distributions. We describe a simulation-based criterion for deciding when to use bias corrections. Various real data sets are used to illustrate the practical application of the suggested bias corrected procedures.
Citation: Sociological Methods & Research
PubDate: 2023-05-25T08:34:43Z
DOI: 10.1177/00491241231176847
- Fieldwork Disrupted: How Researchers Adapt to Losing Access to Field Sites
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Authors: Eric W. Schoon
Abstract: Sociological Methods & Research, Ahead of Print.
This article explores how researchers adapt to disruptions that cost them access to their field sites, advancing a uniquely sociological perspective on the dynamics of flexibility and adaptation in qualitative methods. Through interviews with 31 ethnographers whose access was preempted or eliminated, I find that adaptation varied systematically based on when during the fieldwork process researchers' access was disrupted. The timing of the disruption shaped the relevance and implications of common conditions that affect fieldwork, such as funding availability, institutionalized time constraints, and sunk costs. Consequently, despite a lack of common conventions or training in how to adapt to losing access, adaptations took one of three general forms, which I refer to as turning home, pivoting, and following. I highlight specific challenges associated with each of these forms and offer insights for navigating them. Building from my findings, I make the case that the logistics of being flexible and adapting are part of a hidden curriculum in qualitative methods, and I discuss how interrogating the conditions that structure these aspects of fieldwork advances research and pedagogy in qualitative methodology.
Citation: Sociological Methods & Research
PubDate: 2023-05-19T06:55:20Z
DOI: 10.1177/00491241231156961
- Curating Training Data for Reliable Large-Scale Visual Data Analysis:
Lessons from Identifying Trash in Street View Imagery-
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Authors: Jackelyn Hwang, Nima Dahir, Mayuka Sarukkai, Gabby Wright
Abstract: Sociological Methods & Research, Ahead of Print.
Visual data have dramatically increased in quantity in the digital age, presenting new opportunities for social science research. However, the extensive time and labor costs to process and analyze these data with existing approaches limit their use. Computer vision methods hold promise but often require large and nonexistent training data to identify sociologically relevant variables. We present a cost-efficient method for curating training data that utilizes simple tasks and pairwise comparisons to interpret and analyze visual data at scale using computer vision. We apply our approach to the detection of trash levels across space and over time in millions of street-level images in three physically distinct US cities. By comparing to ratings produced in a controlled setting and utilizing computational methods, we demonstrate generally high reliability in the method and identify sources that limit it. Altogether, this approach expands how visual data can be used at a large scale in sociology.
Citation: Sociological Methods & Research
PubDate: 2023-05-15T06:55:31Z
DOI: 10.1177/00491241231171945
- Longitudinal QCA: Integrating Time Through Change-Based Intervals (CBIs)
and a Flexible Lag Condition (FLC)-
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Authors: Christoph Niessen
Abstract: Sociological Methods & Research, Ahead of Print.
In the wake of the methodological developments that aim to render qualitative comparative analysis (QCA) “time sensitive”, I propose a new procedure for carrying out QCA longitudinally. More specifically, I show first why longitudinal case disaggregation should be carried out with change-based intervals (CBIs) rather than with fixed intervals. Second, I develop a flexible lag condition (FLC) that (i) resolves two types of temporal contradictions and outcome redundancies that can result from temporal case disaggregation and (ii) allows to measure the average duration it takes for a combination of conditions to translate to an outcome. Since temporal contradictions and outcome redundancies are most likely with an increasing number of time points and conditions, as well as with CBIs in general, the FLC procedure is most useful in these cases. The fact that the interest of longitudinal analyses increases with the number of disaggregated cases underlines the usefulness of the proposed methodological innovation. Despite its suitability for mid-n and large-n analyses, longitudinal QCA with an FLC preserves a strong case-oriented and qualitative perspective and remains thereby loyal to QCA's original foundations.
Citation: Sociological Methods & Research
PubDate: 2023-04-25T07:24:17Z
DOI: 10.1177/00491241231156967
- A Method for Estimating Individual Socioeconomic Status of Twitter Users
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Authors: Yuanmo He, Milena Tsvetkova
Abstract: Sociological Methods & Research, Ahead of Print.
The rise of social media has opened countless opportunities to explore social science questions with new data and methods. However, research on socioeconomic inequality remains constrained by limited individual-level socioeconomic status (SES) measures in digital trace data. Following Bourdieu, we argue that the commercial and entertainment accounts Twitter users follow reflect their economic and cultural capital. Adapting a political science method for inferring political ideology, we use correspondence analysis to estimate the SES of 3,482,652 Twitter users who follow the accounts of 339 brands in the United States. We validate our estimates with data from the Facebook Marketing application programming interface, self-reported job titles on users’ Twitter profiles, and a small survey sample. The results show reasonable correlations with the standard proxies for SES, alongside much weaker or nonsignificant correlations with other demographic variables. The proposed method opens new opportunities for innovative social research on inequality on Twitter and similar online platforms.
Citation: Sociological Methods & Research
PubDate: 2023-04-17T04:36:04Z
DOI: 10.1177/00491241231168665
- The Effects of Omitting Components in a Multilevel Model With Social
Network Effects-
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Authors: Thomas Suesse, David Steel, Mark Tranmer
Abstract: Sociological Methods & Research, Ahead of Print.
Multilevel models are often used to account for the hierarchical structure of social data and the inherent dependencies to produce estimates of regression coefficients, variance components associated with each level, and accurate standard errors. Social network analysis is another important approach to analysing complex data that incoproate the social relationships between a number of individuals. Extended linear regression models, such as network autoregressive models, have been proposed that include the social network information to account for the dependencies between persons. In this article, we propose three types of models that account for both the multilevel structure and the social network structure together, leading to network autoregressive multilevel models. We investigate theoretically and empirically, using simulated data and a data set from the Dutch Social Behavior study, the effect of omitting the levels and the social network on the estimates of the regression coefficients, variance components, network autocorrelation parameter, and standard errors.
Citation: Sociological Methods & Research
PubDate: 2023-03-15T10:58:29Z
DOI: 10.1177/00491241231156972
- Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using
Optimal Transport and Conformal Prediction Sets-
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Authors: Richard A. Berk, Arun Kumar Kuchibhotla, Eric Tchetgen Tchetgen
Abstract: Sociological Methods & Research, Ahead of Print.
In the United States and elsewhere, risk assessment algorithms are being used to help inform criminal justice decision-makers. A common intent is to forecast an offender’s “future dangerousness.” Such algorithms have been correctly criticized for potential unfairness, and there is an active cottage industry trying to make repairs. In this paper, we use counterfactual reasoning to consider the prospects for improved fairness when members of a disadvantaged class are treated by a risk algorithm as if they are members of an advantaged class. We combine a machine learning classifier trained in a novel manner with an optimal transport adjustment for the relevant joint probability distributions, which together provide a constructive response to claims of bias-in-bias-out. A key distinction is made between fairness claims that are empirically testable and fairness claims that are not. We then use confusion tables and conformal prediction sets to evaluate achieved fairness for estimated risk. Our data are a random sample of 300,000 offenders at their arraignments for a large metropolitan area in the United States during which decisions to release or detain are made. We show that substantial improvement in fairness can be achieved consistently with a Pareto improvement for legally protected classes.
Citation: Sociological Methods & Research
PubDate: 2023-03-13T08:51:09Z
DOI: 10.1177/00491241231155883
- Inter-Rater Reliability Methods in Qualitative Case Study Research
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Authors: Rosanna Cole
Abstract: Sociological Methods & Research, Ahead of Print.
The use of inter-rater reliability (IRR) methods may provide an opportunity to improve the transparency and consistency of qualitative case study data analysis in terms of the rigor of how codes and constructs have been developed from the raw data. Few articles on qualitative research methods in the literature conduct IRR assessments or neglect to report them, despite some disclosure of multiple researcher teams and coding reconciliation in the work. The article argues that the in-depth discussion and reconciliation initiated by IRR may enhance the findings and theory that emerges from qualitative case study data analysis, where the main data source is often interview transcripts or field notes. To achieve this, the article provides a missing link in the literature between data gathering and analysis by expanding an existing process model from five to six stages. The article also identifies seven factors that researchers can consider to determine the suitability of IRR to their work and it offers an IRR checklist, thereby providing a contribution to the broader literature on qualitative research methods.
Citation: Sociological Methods & Research
PubDate: 2023-02-23T07:14:56Z
DOI: 10.1177/00491241231156971
- Video Data Analysis and Police Body-Worn Camera Footage
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Authors: John D. McCluskey, Craig D. Uchida
Abstract: Sociological Methods & Research, Ahead of Print.
Video data analysis (VDA) represents an important methodological framework for contemporary research approaches to the myriad of footage available from cameras, devices, and phones. Footage from police body-worn cameras (BWCs) is anticipated to be a widely available platform for social science researchers to scrutinize the interactions between police and citizens. We examine issues of validity and reliability as related to BWCs in the context of VDA, based on an assessment of the quality of audio and video obtained from that platform. Second, we compare the coding of BWC footage obtained from a sample of police-citizen encounters to coding of the same events by on-scene coders using an instrument adapted from in-person systematic social observations (SSOs). Findings show that there are substantial and systematic audio and video gaps present in BWC footage as a source of data for social science investigation that likely impact the reliability of measures. Despite these problems, BWC data have substantial capacity for judging sequential developments, causal ordering, and the duration of events. Thus, the technology should open theoretical frames that are too cumbersome for in-person observation. Theoretical development with VDA in mind is suggested as an important pathway for future researchers in terms of framing data collection from BWCs and also suggesting areas where triangulation is essential.
Citation: Sociological Methods & Research
PubDate: 2023-02-20T08:53:07Z
DOI: 10.1177/00491241231156968
- 3D Social Research: Analysis of Social Interaction Using Computer Vision
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Authors: Yoav Goldstein, Nicolas M. Legewie, Doron Shiffer-Sebba
Abstract: Sociological Methods & Research, Ahead of Print.
Video data offer important insights into social processes because they enable direct observation of real-life social interaction. Though such data have become abundant and increasingly accessible, they pose challenges to scalability and measurement. Computer vision (CV), i.e., software-based automated analysis of visual material, can help address these challenges, but existing CV tools are not sufficiently tailored to analyze social interactions. We describe our novel approach, “3D social research” (3DSR), which uses CV and 3D camera footage to study kinesics and proxemics, two core elements of social interaction. Using eight videos of a scripted interaction and five real-life street scene videos, we demonstrate how 3DSR expands sociologists’ analytical toolkit by facilitating a range of scalable and precise measurements. We specifically emphasize 3DSR's potential for analyzing physical distance, movement in space, and movement rate – important aspects of kinesics and proxemics in interactions. We also assess data reliability when using 3DSR.
Citation: Sociological Methods & Research
PubDate: 2023-02-15T05:51:02Z
DOI: 10.1177/00491241221147495
- Book Review: Qualitative Literacy: A Guide to Evaluating Ethnographic and
Interview Research by Small, M.S. and Calarco McCrory, J.-
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Authors: Iddo Tavory
Abstract: Sociological Methods & Research, Ahead of Print.
Citation: Sociological Methods & Research
PubDate: 2023-02-03T08:44:51Z
DOI: 10.1177/00491241221140431
- Estimating Causal Effects of Multi-Valued Treatments Accounting for
Network Interference: Immigration Policies and Crime Rates-
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Authors: Costanza Tortú, Irene Crimaldi, Fabrizia Mealli, Laura Forastiere
Abstract: Sociological Methods & Research, Ahead of Print.
Policy evaluation studies, which assess the effect of an intervention, face statistical challenges: in real-world settings treatments are not randomly assigned and the analysis might be complicated by the presence of interference among units. Researchers have started to develop methods that allow to manage spillovers in observational studies; recent works focus primarily on binary treatments. However, many studies deal with more complex interventions. For instance, in political science, evaluating the impact of policies implemented by administrative entities often implies a multi-valued approach, as a policy towards a specific issue operates at many levels and can be defined along multiple dimensions. In this work, we extend the statistical framework about causal inference under network interference in observational studies, allowing for a multi-valued individual treatment and an interference structure shaped by a weighted network. The estimation strategy relies on a joint multiple generalized propensity score and allows one to estimate direct effects, controlling for both individual and network covariates. We follow this methodology to analyze the impact of the national immigration policy on the crime rate, analyzing data of 22 OECD countries over a thirty-years time frame. We define a multi-valued characterization of political attitude towards migrants and we assume that the extent to which each country can be influenced by another country is modeled by an indicator, summarizing their cultural and geographical proximity. Results suggest that implementing a highly restrictive immigration policy leads to an increase of the crime rate and the estimated effect is larger if we account for interference.
Citation: Sociological Methods & Research
PubDate: 2023-01-09T08:24:55Z
DOI: 10.1177/00491241221147503
- Modeling the Bias of Digital Data: An Approach to Combining Digital With
Official Statistics to Estimate and Predict Migration Trends-
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Authors: Yuan Hsiao, Lee Fiorio, Jonathan Wakefield, Emilio Zagheni
Abstract: Sociological Methods & Research, Ahead of Print.
Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for combining digital data and official statistics by using the official statistics to model the spatial and temporal dependence structure of the biases of digital data. We use simulations to demonstrate the validity of the model, then empirically illustrate our approach by combining geo-located Twitter data with data from the American Community Survey (ACS) to estimate state-level out-migration probabilities in the United States. We show that our model, which combines unbiased and biased data, produces predictions that are more accurate than predictions based solely on unbiased data. Our approach demonstrates how digital data can be used to complement, rather than replace, official statistics.
Citation: Sociological Methods & Research
PubDate: 2023-01-02T11:37:55Z
DOI: 10.1177/00491241221140144
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Hybrid journal (It can contain Open Access articles)
