Matthew DeBell, D Sunshine Hillygus, Daron R Shaw, Nicholas A Valentino
{"title":"验证 \"真实管道 \"以限制选民投票率调查估计中的社会期望偏差","authors":"Matthew DeBell, D Sunshine Hillygus, Daron R Shaw, Nicholas A Valentino","doi":"10.1093/poq/nfae007","DOIUrl":null,"url":null,"abstract":"It is well documented that survey overreporting of voter turnout due to social desirability bias threatens inference about political behavior. This paper reports four studies that contained question wording experiments to test questions designed to minimize that bias using a “pipeline” approach. The “pipeline” informs survey participants that researchers can perform vote validation to verify turnout self-reports. This approach reduced self-reported turnout by 5.7 points in the 2020 American National Election Study, which represents a majority of the estimated overreporting bias. It reduced reported turnout by 4 points in two nonprobability samples. No effect was found in a third nonprobability study with Amazon Mechanical Turk workers. Validated vote data also confirm that the pipeline approach reduced overreporting. We tested heterogeneous effects for sophistication and several other variables, but results were inconclusive. The pipeline approach reduces overreporting of voter turnout and produces more accurate estimates of voters’ characteristics.","PeriodicalId":51359,"journal":{"name":"Public Opinion Quarterly","volume":"31 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Validating the “Genuine Pipeline” to Limit Social Desirability Bias in Survey Estimates of Voter Turnout\",\"authors\":\"Matthew DeBell, D Sunshine Hillygus, Daron R Shaw, Nicholas A Valentino\",\"doi\":\"10.1093/poq/nfae007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is well documented that survey overreporting of voter turnout due to social desirability bias threatens inference about political behavior. This paper reports four studies that contained question wording experiments to test questions designed to minimize that bias using a “pipeline” approach. The “pipeline” informs survey participants that researchers can perform vote validation to verify turnout self-reports. This approach reduced self-reported turnout by 5.7 points in the 2020 American National Election Study, which represents a majority of the estimated overreporting bias. It reduced reported turnout by 4 points in two nonprobability samples. No effect was found in a third nonprobability study with Amazon Mechanical Turk workers. Validated vote data also confirm that the pipeline approach reduced overreporting. We tested heterogeneous effects for sophistication and several other variables, but results were inconclusive. The pipeline approach reduces overreporting of voter turnout and produces more accurate estimates of voters’ characteristics.\",\"PeriodicalId\":51359,\"journal\":{\"name\":\"Public Opinion Quarterly\",\"volume\":\"31 1\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Public Opinion Quarterly\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1093/poq/nfae007\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Public Opinion Quarterly","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1093/poq/nfae007","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
Validating the “Genuine Pipeline” to Limit Social Desirability Bias in Survey Estimates of Voter Turnout
It is well documented that survey overreporting of voter turnout due to social desirability bias threatens inference about political behavior. This paper reports four studies that contained question wording experiments to test questions designed to minimize that bias using a “pipeline” approach. The “pipeline” informs survey participants that researchers can perform vote validation to verify turnout self-reports. This approach reduced self-reported turnout by 5.7 points in the 2020 American National Election Study, which represents a majority of the estimated overreporting bias. It reduced reported turnout by 4 points in two nonprobability samples. No effect was found in a third nonprobability study with Amazon Mechanical Turk workers. Validated vote data also confirm that the pipeline approach reduced overreporting. We tested heterogeneous effects for sophistication and several other variables, but results were inconclusive. The pipeline approach reduces overreporting of voter turnout and produces more accurate estimates of voters’ characteristics.
期刊介绍:
Published since 1937, Public Opinion Quarterly is among the most frequently cited journals of its kind. Such interdisciplinary leadership benefits academicians and all social science researchers by providing a trusted source for a wide range of high quality research. POQ selectively publishes important theoretical contributions to opinion and communication research, analyses of current public opinion, and investigations of methodological issues involved in survey validity—including questionnaire construction, interviewing and interviewers, sampling strategy, and mode of administration. The theoretical and methodological advances detailed in pages of POQ ensure its importance as a research resource.