{"title":"网络社会阶层线索与就业能力:来自德国的实验证据","authors":"Diana Roxana Galos , Joris Frese","doi":"10.1016/j.ssresearch.2025.103258","DOIUrl":null,"url":null,"abstract":"<div><div>Social media platforms, such as Twitter or Instagram, offer easily accessible information – relevant or not – for employers when evaluating candidates for a position. In particular, they tend to be sources of information about individuals’ interests and leisure activities. Because interests are highly stratified by social class (e.g., engagement in highbrow and lowbrow activities), this represents a new way for class to potentially manifest itself in the hiring process. To study discrimination in hiring based on online social class cues, we conducted a pre-registered survey experiment in Germany with samples of employers and non-employers, manipulating job applicants’ class cues on social media (highbrow versus lowbrow). Overall, we found no difference in preferences for the candidates displaying highbrow and lowbrow activities on their social media profiles. However, this masks important differences in the specific activities proxying for class. When these activities have no relevance for the jobs in question, higher-class candidates are preferred. Exploratory analyses show that respondents are more likely to express positive sentiments toward the higher-class profiles, with highbrow activities being positively associated with work-related traits. Our findings highlight the need to consider how digital environments and, more specifically, online social class cues, may contribute to class bias in hiring.</div></div>","PeriodicalId":48338,"journal":{"name":"Social Science Research","volume":"133 ","pages":"Article 103258"},"PeriodicalIF":3.5000,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Online social class cues and employability: Experimental evidence from Germany\",\"authors\":\"Diana Roxana Galos , Joris Frese\",\"doi\":\"10.1016/j.ssresearch.2025.103258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Social media platforms, such as Twitter or Instagram, offer easily accessible information – relevant or not – for employers when evaluating candidates for a position. In particular, they tend to be sources of information about individuals’ interests and leisure activities. Because interests are highly stratified by social class (e.g., engagement in highbrow and lowbrow activities), this represents a new way for class to potentially manifest itself in the hiring process. To study discrimination in hiring based on online social class cues, we conducted a pre-registered survey experiment in Germany with samples of employers and non-employers, manipulating job applicants’ class cues on social media (highbrow versus lowbrow). Overall, we found no difference in preferences for the candidates displaying highbrow and lowbrow activities on their social media profiles. However, this masks important differences in the specific activities proxying for class. When these activities have no relevance for the jobs in question, higher-class candidates are preferred. Exploratory analyses show that respondents are more likely to express positive sentiments toward the higher-class profiles, with highbrow activities being positively associated with work-related traits. Our findings highlight the need to consider how digital environments and, more specifically, online social class cues, may contribute to class bias in hiring.</div></div>\",\"PeriodicalId\":48338,\"journal\":{\"name\":\"Social Science Research\",\"volume\":\"133 \",\"pages\":\"Article 103258\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Social Science Research\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0049089X2500119X\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Science Research","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0049089X2500119X","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIOLOGY","Score":null,"Total":0}
Online social class cues and employability: Experimental evidence from Germany
Social media platforms, such as Twitter or Instagram, offer easily accessible information – relevant or not – for employers when evaluating candidates for a position. In particular, they tend to be sources of information about individuals’ interests and leisure activities. Because interests are highly stratified by social class (e.g., engagement in highbrow and lowbrow activities), this represents a new way for class to potentially manifest itself in the hiring process. To study discrimination in hiring based on online social class cues, we conducted a pre-registered survey experiment in Germany with samples of employers and non-employers, manipulating job applicants’ class cues on social media (highbrow versus lowbrow). Overall, we found no difference in preferences for the candidates displaying highbrow and lowbrow activities on their social media profiles. However, this masks important differences in the specific activities proxying for class. When these activities have no relevance for the jobs in question, higher-class candidates are preferred. Exploratory analyses show that respondents are more likely to express positive sentiments toward the higher-class profiles, with highbrow activities being positively associated with work-related traits. Our findings highlight the need to consider how digital environments and, more specifically, online social class cues, may contribute to class bias in hiring.
期刊介绍:
Social Science Research publishes papers devoted to quantitative social science research and methodology. The journal features articles that illustrate the use of quantitative methods in the empirical solution of substantive problems, and emphasizes those concerned with issues or methods that cut across traditional disciplinary lines. Special attention is given to methods that have been used by only one particular social science discipline, but that may have application to a broader range of areas.