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Authors:Sophie Duchesne Pages: 3 - 5 Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Volume 154, Issue 1, Page 3-5, April 2022.
Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2022-05-13T03:43:44Z DOI: 10.1177/07591063221088313 Issue No:Vol. 154, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Sophie Duchesne Pages: 6 - 8 Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Volume 154, Issue 1, Page 6-8, April 2022.
Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2022-05-13T03:42:39Z DOI: 10.1177/07591063221088313a Issue No:Vol. 154, No. 1 (2022)
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Authors:Don A. Dillman Pages: 9 - 38 Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Volume 154, Issue 1, Page 9-38, April 2022. While completing my PhD in sociology, I did not anticipate spending most of my academic career researching ways to improve methods for doing sample surveys. At that time, I was dedicated to understanding community organization and how people adopt the use of new technologies. This article describes how becoming a new assistant professor just prior to a university crisis turned my academic interests away from organizational behavior toward more than five decades of research to advance survey methodology in step with technological changes transforming the world. This process also turned upside down my thoughts on how to do research. Increasingly I was inspired by the work of survey designers in government and private sector organizations who needed help with improving their survey designs. These experiences led to the creation of a series of innovations: telephone and mail data collection methods, mixed-mode surveying, tailored design for different survey situations, data collection over the internet, unified construction of questionnaires across survey modes, and understanding the differences between answers given to aurally vs. visually delivered survey questions. This sequence of research efforts led to the development and testing of web-push procedures that are now replacing the use of telephone survey methods throughout the world. Yet frequently and at unexpected times, my education in social organization and technology issues provided much needed guidance for thinking beyond the constraints of current survey methods and the possibilities that new methods could provide. Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2022-05-13T03:43:44Z DOI: 10.1177/07591063221088317 Issue No:Vol. 154, No. 1 (2022)
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Authors:Maren Toft Pages: 105 - 132 Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Volume 154, Issue 1, Page 105-132, April 2022. In this article, I discuss the potential for quantitatively accounting of the social world as relationally constituted in both a topological and a temporal sense. As statistical procedures rest on underlying assumptions of the social world, I emphasise how multiple correspondence analysis (MCA) thinks relationally, as Bourdieu famously proclaimed, but to a lesser extent addresses the temporal pattering of social life. I point to the beneficial property of sequence analysis (SA) in thinking ‘processually’, and I argue that the combination of the two tools stimulates favourable opportunities for relational thinking in complementary ways. While adding SA to MCA inserts processual thinking into a relational space, the MCA helps embedding sequential patterns within a social structure. I critically assess this strategy by drawing on the diachronic underpinnings to Pierre Bourdieu’s oeuvre and empirically examine how his third dimension of social space – trajectory – might be ‘quantified’. Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2022-05-13T03:42:37Z DOI: 10.1177/07591063221088321 Issue No:Vol. 154, No. 1 (2022)
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Authors:Karl van Meter Pages: 133 - 139 Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Volume 154, Issue 1, Page 133-139, April 2022.
Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2022-05-13T03:43:44Z DOI: 10.1177/07591063221088318 Issue No:Vol. 154, No. 1 (2022)
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Authors:David Descamps, Agathe Foudi First page: 39 Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Ahead of Print. Bringing to light income and diploma inequalities. On the ‘stratificationist’ efficiency of the PCS Classification, the ESeG classification and the Employment class schema. Occupational classifications are among the main tools for objectivizing the structure of a society and they are sometimes used to grasp the inequalities within it. This paper aims at offering several indicators designed to assess occupational classifications’ ability to shed light on the unequal distribution of resources between social groups. Three classifications are here studied: the French PCS-2003 and the French Employment class schema from INSEE and the European ESeG classification. After recalling their principles and objectives, we lay down the usual procedures used to assess occupational classifications and we show that they don’t aim to grasp their ability to reflect social stratification. Using fractiles, which are commonly-used tool for analysing inequalities, we then offer two sets of indicators designed to assess the occupational classifications’ efficiency to reflect the slope, the shape and the extent of the inequalities in a population. Using these tools and data from the 2017 French Labour Force Survey, we show that at the aggregate level of the classifications studied, it is the four Employment class schema that best captures the unequal distribution of income and diplomas between population groups, whereas at the detailed level, it is rather the PCS. We finally put forward proposals for recomposing some of the categories of the PCS and the Employment class schema so as to make these classifications more efficient to reflect social stratification. Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2022-01-24T11:10:21Z DOI: 10.1177/07591063211061755
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Authors:Zoltán Kmetty, Renáta Németh First page: 82 Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Ahead of Print. In this study, we use a parallel mixed-method data collection: a face-to-face survey combined with personal Facebook data archive collection. Our paper is the first attempt to cross-validate the self-reported musical preference with Facebook-based music preference classification. We primarily focused on operationalization-related questions and validity issues.The results overall showed that the different measures have only moderate correlations with each other. Some genres measured similarly, but there were significant differences too. A good example of the latter is world-music. It was the second most preferred genre of the survey, but based on FB data it was at the lower end of the preference scale.Digital data opens the possibility of examining topics we could not investigate, and re-examining topics with new approaches. However, all the data sources have their validity problems, and we need to consider many factors before we select a data source for analysis. Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2022-01-24T11:09:40Z DOI: 10.1177/07591063211061754
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Ahead of Print.
Citation: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique PubDate: 2021-12-21T09:46:54Z DOI: 10.1177/07591063211066008
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