Occupational Classifications and Derived Status Indices: Challenges and New Approaches 2 |
|
| Coordinator 1 | Dr Christoph Homuth (Leibniz Institute for Educational Trajectories) |
| Coordinator 2 | Professor Corinna Kleinert (Leibniz Institute for Educational Trajectories) |
| Coordinator 3 | Dr Ann-Christin Bächmann (Leibniz Institute for Educational Trajectories) |
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 Occupational classifications and derived indices might be quickly outdated in times of rapid occupational and social change.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