{"title":"调查中的社会人口变量通过产出协调增加研究潜力","authors":"Silke Schneider, Lennart Palm","doi":"10.52825/cordi.v1i.306","DOIUrl":null,"url":null,"abstract":"Measuring people’s sociodemographic characteristics over time and in different contexts or studies is one of the keys of quantifying social inequalities and social change within any society. While different respondent-based studies usually focus on different topics, almost all of them collect data on some key features defining respondent’s backgrounds and living situations.\nSummarizing the measurement of sociodemographic characteristics however, the German survey landscape could be characterized as “same but different”: studies measure the same concepts yet differ in their specific approach, despite the fact that the “Demographische Standards” (Hoffmeyer-Zlotnik et al., 2016) provide recommended questionnaire items since the early 1990s. This has several problematic implications: Firstly, it becomes quite difficult to combine knowledge about groups of respondents with the same sociodemographic characteristics across studies on a macro level, and thus to systematically accumulate knowledge on social inequalities and social change. Secondly, combining different data sets, e.g. in order to be able to analyze small groups or rare phenomena, can become a laborious effort which might still produce questionable results, since key caveats can be overlooked in survey documentation.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sociodemographic Variables in Surveys Increasing Research Potential Through Output Harmonization\",\"authors\":\"Silke Schneider, Lennart Palm\",\"doi\":\"10.52825/cordi.v1i.306\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Measuring people’s sociodemographic characteristics over time and in different contexts or studies is one of the keys of quantifying social inequalities and social change within any society. While different respondent-based studies usually focus on different topics, almost all of them collect data on some key features defining respondent’s backgrounds and living situations.\\nSummarizing the measurement of sociodemographic characteristics however, the German survey landscape could be characterized as “same but different”: studies measure the same concepts yet differ in their specific approach, despite the fact that the “Demographische Standards” (Hoffmeyer-Zlotnik et al., 2016) provide recommended questionnaire items since the early 1990s. This has several problematic implications: Firstly, it becomes quite difficult to combine knowledge about groups of respondents with the same sociodemographic characteristics across studies on a macro level, and thus to systematically accumulate knowledge on social inequalities and social change. Secondly, combining different data sets, e.g. in order to be able to analyze small groups or rare phenomena, can become a laborious effort which might still produce questionable results, since key caveats can be overlooked in survey documentation.\",\"PeriodicalId\":359879,\"journal\":{\"name\":\"Proceedings of the Conference on Research Data Infrastructure\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Conference on Research Data Infrastructure\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52825/cordi.v1i.306\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Conference on Research Data Infrastructure","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52825/cordi.v1i.306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
衡量人们随时间和不同背景或研究的社会人口特征是量化任何社会中社会不平等和社会变化的关键之一。虽然不同的基于受访者的研究通常关注不同的主题,但几乎所有的研究都收集了定义受访者背景和生活状况的一些关键特征的数据。然而,总结社会人口特征的测量,德国的调查景观可以被描述为“相同但不同”:研究测量相同的概念,但具体方法不同,尽管“人口标准”(Hoffmeyer-Zlotnik et al., 2016)自20世纪90年代初以来提供了推荐的问卷项目。这有几个问题的含义:首先,很难在宏观层面上将调查对象群体的知识与相同的社会人口特征结合起来,从而系统地积累关于社会不平等和社会变化的知识。其次,结合不同的数据集,例如为了能够分析小群体或罕见现象,可能会成为一项费力的工作,可能仍然会产生可疑的结果,因为在调查文档中可能会忽略关键的警告。
Sociodemographic Variables in Surveys Increasing Research Potential Through Output Harmonization
Measuring people’s sociodemographic characteristics over time and in different contexts or studies is one of the keys of quantifying social inequalities and social change within any society. While different respondent-based studies usually focus on different topics, almost all of them collect data on some key features defining respondent’s backgrounds and living situations.
Summarizing the measurement of sociodemographic characteristics however, the German survey landscape could be characterized as “same but different”: studies measure the same concepts yet differ in their specific approach, despite the fact that the “Demographische Standards” (Hoffmeyer-Zlotnik et al., 2016) provide recommended questionnaire items since the early 1990s. This has several problematic implications: Firstly, it becomes quite difficult to combine knowledge about groups of respondents with the same sociodemographic characteristics across studies on a macro level, and thus to systematically accumulate knowledge on social inequalities and social change. Secondly, combining different data sets, e.g. in order to be able to analyze small groups or rare phenomena, can become a laborious effort which might still produce questionable results, since key caveats can be overlooked in survey documentation.