The paper argues for the value of conducting surveys in vulnerable neighborhoods and provides a detailed account of a cost-effective strategy for surveying a recognized hard-to-survey population. The approach is illustrated through insights from the Vulnerable Neighborhoods Survey, conducted in three Nordic countries. The strategy focuses on a small number of specific neighborhoods and implements a range of measures to lower participation barriers. A key component involves combining random and non-random sampling techniques to facilitate the recruitment of a broad segment of residents. According to comparisons with registry data, the strategy produces samples that resemble the population on multiple demographic factors.
Randomized paired comparisons (RPC) for social values have various advantages over a matrix format of multiple items; however, their use cannot exhaust all possible pairs if there are too many items to compare one-to-one. This article proposes (1) applying a dimension reduction method, structural topic modeling (STM), to RPC survey data by restructuring answers into ordered pairs to estimate latent answering patterns, (2) visualizing them into directed graphs, and (3) interpreting them as respondents’ preference structures among social values. For empirical validation, we randomly divided 920 respondents into RPC and matrix-format groups and asked about the seriousness of ten social problems. Our STM from the RPC group revealed five preference structures beyond a linear order among the 10 items, which are interpretable and incorporate statistical tests with respondents’ traits as covariates. We also discuss how to improve topic modeling with RPC and contribute to various research streams, such as cultural value networks and gamification, by pairwise wiki survey.
A series of papers uses administrative data on school students’ grades to assess whether teachers discriminate against certain demographic groups. Often, differences in teacher and test grades are regressed on student-level variables. However, it is unclear under what circumstances such an estimation strategy is valid. We conceptualize teacher bias as a direct causal effect of student-level attributes on teacher grades, fixing student ability. Standardized tests merely proxy for student ability; additionally, there may be confounders of ability and teacher grade. Accordingly, teacher bias is nonparametrically unidentified. However, we suggest substantive and parametric assumptions that ensure identification using difference-in-grades estimators. Estimators based on regression control for test grades are shown to be inconsistent even under these strong assumptions. We then develop a parametric sensitivity analysis that allows researchers to investigate the consequences of departures from critical assumptions. We illustrate our methodology using administrative data from Denmark.
Estimating the size of the undocumented migrant population remains a critical challenge for researchers and policymakers. This study assesses the viability of using social media platforms, specifically Facebook and Instagram, to recruit a survey sample of migrants and elicit their status. The research focuses on Mexican and Venezuelan immigrants in Texas, Florida, Illinois, and California. Three methods for eliciting legal status are tested: direct questions, indirect sequential questions (stepwise exclusion), and a list experiment. The study ( N = 2,027) finds that while social media recruitment is cost-effective and rapid, it faces challenges such as selection bias, misclassification, and platform-imposed restrictions. The list experiment suggests the presence of response bias in traditional surveys to sensitive legal status questions. Estimates of the share of undocumented migrants deviate considerably from available reference estimates. We argue that social media surveys are best applied in preparation for traditional surveys rather than in their place.
This research evaluates methodologies to mitigate misreporting in intimate partner violence (IPV) data collection in a middle-income country. We conducted surveys in Russia involving three list experiments, a self-administered tablet questionnaire, a self-administered online survey, and conventional face-to-face interviews. Results show that list experiments yield lower disclosure rates for the complex IPV definitions suggested by the UN. The tablet-based self-administered questionnaire, conducted with an interviewer present, also did not increase IPV reporting. Conversely, the self-administered online survey increased lifetime IPV disclosures by 51% (physical) and 26% (psychological) compared to face-to-face interviews. Women showed greater sensitivity to the online survey mode. This increase is linked to the absence of interviewer bias, enhanced safety by minimizing potential perpetrators' presence, and reduced cognitive burden. We argue that self-administered online surveys-using sampling bias mitigation-may thus be an optimal, low-cost method for surveying the general population in middle- and high-income countries.
