All time references are in CEST
Occupational Classifications and Derived Status Indices: Challenges and New Approaches 2 |
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| Session Organisers |
Dr Christoph Homuth (Leibniz Institute for Educational Trajectories) Professor Corinna Kleinert (Leibniz Institute for Educational Trajectories) Dr Ann-Christin Bächmann (Leibniz Institute for Educational Trajectories) |
| Time | Wednesday 19 July, 16:00 - 17:30 |
| Room | U6-02 |
Occupations are important indicators of economic, cultural, and social capital, social status, prestige and class, as well as predictors of future life chances and security. They are associated with particular working conditions, gender types, interests and tasks, as well as with macro-level phenomena such as occupational segregation, segmentation, and closure.
Therefore, it is essential to gather valid and reliable information on occupations in surveys, which then is coded into occupational classifications (e.g., ISCO) that allow examining occupations and deriving social status indicators (e.g., ISEI, EGP).
Measuring and analyzing occupations and derived indices is challenging: coding in surveys is resource-intensive and error-prone due to occupational complexity and incorrect or incomplete data. Hence, automation methods are searched for, which have to be adapted to new survey modes. Different data sources (e.g., survey and administrative data) might produce different measurement errors. Occupational classifications and derived indices might be quickly outdated in times of rapid occupational and social change. Different cultural, economic, and institutional settings challenge the harmonization and comparison of occupational classifications and status indices in international comparative research.
In this session, we aim to bring together researchers interested in:
- advancements in occupational coding (e.g., automatic coding, machine learning)
- new ways of collecting occupational information, especially in the context of changing
survey modes (e.g., more online surveys or app-based data collection)
- innovative measurement approaches to collecting information on established occupational
classifications and scales
- adaptation of and innovation in occupational classifications
- temporal stability of occupational classifications
- cross-national comparisons and harmonization of classifications and indices
- comparisons of occupational codes in linked data sets (e.g., survey and administrative
data) to assess data quality
- other theoretical or methodological aspects related to occupational classifications and
derived status indices
Keywords: Occupations, Coding, Occupational Classifications, Status Indices
Dr Ann-Christin Bächmann (Leibniz Institute for Educational Trajectories)
Dr Basha Vicari (Institute for Employment Research) - Presenting Author
Dr Aline Zucco (Hans Böckler Stiftung)
The German Classification of Occupations 2010 (KldB 2010) does not only provide information on the occupational specialization but also differentiates the occupational units by their level of requirement into four groups ranging from (1) unskilled or semi-skilled activities to (4) highly complex activities (Paulus & Matthes 2013). The requirement level (5th digit of the KldB 2010) offers a new analytical potential to observe the career advancement of workers and to address crucial issues of social inequality, e.g. by analyzing possible gender differences in career paths. So far, however, it is unclear whether the measure of the requirement level and possible changes over time is reliably reported. Depending on the way the occupational information is collected, different types of measurement errors may occur. For instance, survey data can be inaccurate and are prone to coding errors. But administrative data may also be subject to errors, e.g. employer notifications might under-report changes in the annual occupational coding routine, including changes in the requirement level.
In our paper, we investigate these potential sources of error and by comparing information on the requirement level in different German data sources (NEPS-SC6, GSOEP, SIAB, Structure of Earnings Survey). In a second step, we use linked data to examine differences in the reported occupation and especially in the requirement level more closely on the basis of respondent information and employer reports. Therefore, we use the NEPS-SC6-ADIAB that link survey data of the Adult Cohort of the German National Educational Panels Study with administrative data from the Integrated Employment Biographies (IEB) of the Institute for Employment Research. First results suggest that the level of requirement is a comparatively reliable measure for career advancement. Further we find no hints for systematic underestimation of changes in requirement levels in the employer reports.
Dr Jessica Herzing (University of Bern) - Presenting Author
Dr Simon Seiler (University of Bern)
Mr Leo Röhlke (University of Bern)
Dr Andrea Erzinger (University of Bern)
Mr Tobias Ackermann (University of Bern)
The impact of socio-economic status (SES) on educational achievement plays a central role in social stratification research. The measurement of SES characteristics (e.g., parental occupation and the number of books at home) is fundamental for such studies. Whether student respondents can provide valid reports of their parents’ occupation and the number of books at home has been a topic of previous articles. Several student characteristics have been associated with the validity of their response, e.g., the student’s test score (Kreuter et al. 2010). Most previous studies on this topic used data from students 10 years and older, however, the literature suggests that the younger the students, the more error-prone are their reports (Mare & Mason 1980). We contribute to this strand of research by investigating survey data from a large-scale-assessment of 8-year-olds in Switzerland by addressing four research questions:
(1) How does the consistency of students’, parents’, and administrations’ reports on the variable of parental occupation differ?
(2) Is there an association between these consistencies and a student’s test score?
(3) Are the effects of this variable on test scores robust to the different data sources used?
(4) How do the consequences of parental selective nonresponse compare in magnitude with those of student misreporting?
We investigate these questions by analyzing the correspondence of the different data sources, e.g, by reporting Spearman’s p and Cohen’s k. Furthermore, we present differences between student, parent, and administrative data depending on students' test scores. Finally, we discuss the implications of these inconsistencies for commonly used models in education research.
Professor Christian Ebner (Technische Universität Braunschweig) - Presenting Author
Dr Daniela Rohrbach-Schmidt (BIBB Bonn)
An essential function of occupations is to create status differences in society. Socially valued resources such as prestige or income differ markedly depending on the individual's occupation. In addition, significant occupational differences can be observed with respect to job security, emotional or physical stress.
In our paper, we present a representative data collection on the perception of occupations in Germany (year 2017/18). Around 9,000 individuals were asked to assess their perceptions of randomly selected occupations each in terms of the dimensions of prestige, pay, educational requirements, unemployment risk, physical and emotional stress as well as work-life balance. Overall, these perceptions can be analyzed for 402 different occupations.
From the assessments of these occupations, we generate different occupational scales for the most recent German Classification of Occupations (KldB 2010), both at the level of occupational groups and main occupational groups. The scales are assessed along established quality criteria such as validity, objectivity, and reliability. Initial tests of the occupational prestige scale (https://metadaten.bibb.de/de/dataset/detail/BAS) indicate high reliability, content validity, construct validity, and criterion validity.
From a substantive point of view, we demonstrate the possibilities of the dataset by presenting correlations between occupational prestige and the other (perceived) occupational dimensions. To date, analyses explaining occupational prestige have mainly used objective factors for prediction. With our data, there is now the possibility to better address the social construction of occupational prestige from the respondents' point of view. In addition to the classic explanatory factors for occupational prestige - income and education - further criteria used (unemployment risk, physical and emotional stress, work-life balance ) represent a novelty.
Dr Roujman Shahbazian (University of Munich) - Presenting Author
Professor Erik Bihagen (Institute for Social Research (SOFI) at Stockholm University)
Dr Sara Kjellsson (Department of Public Health Sciences)
A common assumption within social mobility research is that the large majority of people reach class/occupational maturity quite early in working life, that is they end up in an occupation/class position that they keep for the remainder of their working life – around age of 35. Put differently, individuals tend to reach occupational maturity early and consequently also their final class of destination as class concepts generally are based on occupations.
Considering the importance of class of destination in intergenerational mobility studies, there are surprisingly few studies that focus on occupational maturation and how this differs across cohorts. The stabilization of careers is also of broader interest from a stratification point of view as it could be argued that the smaller the variation in class across the life course and the quicker a class of destination is reached the better class will predict life chances in one way or another. More generally it could be argued that “any idea of social structure includes the notion of relative stability” (Blossfeld 1986: 208).
We aim to shed light on the stabilization in terms of both occupational prestige (SIOPS) and class (ESeC) across ages (15-64), by using longitudinal occupational biographies in Swedish Level-of-Living Surveys. We compare six cohorts born between 1925 to 1984.
The findings speak against the idea of occupational and class maturity, and consequently point to problems in estimating intergenerational mobility from cross-sectional data. Additionally, occupation and class should not generally be seen as positions of destination from a certain age, but rather as time-varying positions and this points to the need of using longitudinal data.
Research is needed to learn more about country differences in occupational and class maturation and to what extent intergenerational mobility results are actually biased by intragenerational mobility in both
Dr Christoph Homuth (Leibniz Institute for Educational Trajectories (LIfBi)) - Presenting Author
Mr Felix Bittmann (Leibniz Institute for Educational Trajectories (LIfBi))
Mr Gregor Lampel (Leibniz Institute for Educational Trajectories (LIfBi))
Social origin and social status are essential constructs in social science research and are therefore part of virtually all surveys. While there are some operationalizations in closed form, e.g., (parental) educational, books at home, income, many important and widely used social origin or status indices, i.e. socioeconomic (ISEI), prestige scores (SIOPS), or social class (EGP) indices are based on respondents’ occupation and derived from national or international occupational classifications (ISCO).
Measuring social origin is an expensive undertaking because measuring occupations is mostly done via open-ended questions which must be (often manually) coded. Successful coding is highly depended on the answer quality. Another challenge of open-ended questions is the higher rate of item non-response. Therefore, open-ended questions are more often used in interviewer-based survey modes to guarantee a high enough quality. As the prevalence of interviewer-based surveys is declining and online surveys are becoming the norm in social sciences, valid and reliable ways to gather social origin data in (web) questionnaires are needed.
We test the quality of a close-ended measurement of social origin that we used in an online survey with n = 600 parents of secondary school children in Germany. We developed a close-ended measurement for social class that we used in an online-survey alongside traditional questions on occupational status from which were manually coded, and social origin indices derived.
We gauge the quality of this measurement by looking at several dimension: rate of item non-response, answering time, concept validity (correlation with education), and predictive validity (correlation with educational aspirations). Preliminary analyses showed that the closed format had six times more missings than the derived EGP index, the correlation with parental education (on the CASMIN scale) was comparable, and it better predicted parental educational aspirations than the EGP.