Grouping of Occupations Based on Intragenerational Mobility
Abstract
Occupation is a key factor in human thinking, feeling, and behavior. Theoretically derived occupational groupings or classes are typically used to transform occupations into a variable suitable for statistical manipulations. We argue that such groupings are unlikely to produce groups that are homogeneous across a broad set of attributes. Instead, we offer a data-driven approach to identify groups of occupations based on respondents’ mobility data using network analysis. The vertices of the network are codes of occupations, and the edges reflect the number of transitions between them. Using modularity maximization, we identify four communities and evaluate the stability of the resulting partition. As an example demonstrating the efficiency of the resulting grouping, we present a comparison of the predictive power of this grouping and one of the generally accepted groupings of occupations, that is ESeG (European Socio-Economic Grouping), in relation to the human attitudes and values found in previous publications. The results indicate the preference of our grouping.
References
- Adriaenssens, S., Hendrickx, J., & Holm, J. (2022). Class foundations of sexual prejudice toward gay and lesbian people. Sexuality Research and Social Policy, 19(1), 63–84. https://doi.org/10.1007/s13178-020-00525-y
- Bessudnov, A. (2012). A relational occupational scale for Russia. In P. Lambert, R. Connelly, B. Blackburn, & V. Gayle (Eds.), Social stratification: Trends and processes (pp. 53–68). Ashgate.
- Booth, D. E. (2021). Post-materialism’s social class divide: Experiences and life satisfaction. Journal of Human Values, 27(2), 141–160. https://doi.org/10.1177/0971685820946180
- Breiger, R. L. (1981). The social class structure of occupational mobility. American Journal of Sociology, 87(3), 578–611. https://doi.org/10.1086/227497
- Cafieri, S., Hansen, P., & Liberti, L. (2010). Loops and multiple edges in modularity maximization of networks. Physical Review E, 81(4), Article 046102. https://doi.org/10.1103/PhysRevE.81.046102
- Cheng, S., & Park, B. (2020). Flows and boundaries: A network approach to studying occupational mobility in the labor market. American Journal of Sociology, 126(3), 577–631. https://doi.org/10.1086/712406
- Csárdi, G., Nepusz, T., Müller, K., Horvát, S., Traag, V., Zanini, F., & Noom, D. (2023, August 12). igraph for R: R interface of the igraph library for graph theory and network analysis (v1.5.1). Zenodo. https://doi.org/10.5281/zenodo.8240644
- Davidov, E., Cieciuch, J., & Schmidt, P. (2018). The cross-country measurement comparability in the immigration module of the European Social Survey 2014–15. Survey Research Methods, 12(1), 15–27. https://doi.org/10.18148/srm/2018.v12i1.7212
- Davidov, E., Schmidt, P., & Schwartz, S. H. (2008). Bringing values back in: The adequacy of the European Social Survey to measure values in 20 countries. Public Opinion Quarterly, 72(3), 420–445. https://doi.org/10.1093/poq/nfn035
- De Keere, K. (2020). Finding the moral space: Rethinking morality, social class and worldviews. Poetics, 79, Article 101415. https://doi.org/10.1016/j.poetic.2019.101415
- European Social Survey (ESS). (2016). ESS Round 8 source questionnaire. ESS ERIC Headquarters. https://stessrelpubprodwe.blob.core.windows.net/data/round8/fieldwork/source/ESS8_source_questionnaires.pdf
- Goodman, L. A. (1981). Criteria for determining whether certain categories in a cross-classification table should be combined, with special reference to occupational categories in an occupational mobility table. American Journal of Sociology, 87(3), 612–650. https://doi.org/10.1086/227498
- International Labour Organization (ILO). (n.d.). International standard classification of occupations: Brief history. https://www.ilo.org/public/english/bureau/stat/isco/intro2.htm
- International Labour Organization Department of Statistics (ILOSTAT). (n.d.). International standard classification of occupations (ISCO): Classification. https://ilostat.ilo.org/resources/concepts-and-definitions/classification-occupation/
- Kohn, M. (1989). Class and conformity: A study in values. University of Chicago Press.
- Kulin, J., & Svallfors, S. (2013). Class, values, and attitudes towards redistribution: A European comparison. European Sociological Review, 29(2), 155–167. https://doi.org/10.1093/esr/jcr046
- Lambert, P. S., & Griffiths, D. (2018). Social inequalities and occupational stratification: Methods and concepts in the analysis of social distance. Palgrave Macmillan. https://doi.org/10.1057/978-1-137-02253-0
- Meron, M., Amar, M., Laurent-Zuani, A. C., Holý, D., Erhartova, J., Gallo, F., Lindner, E., Záhonyi, M., Váradi, R., Huszár, A., & Franco, A. (2014). Final Report of the ESSnet on the harmonisation and implementation of a European Socio-economic classification: European Socio-economic Groups (EseG). National Institute of Statistics and Economic Studies. https://circabc.europa.eu/sd/a/519eafb9-186c-4e2c-a178-902f28501ba4/DSS-2014-Sep-08c%20ESSnet-ESeG%20-%20Final%20Report.pdf
- Newman, M. E. (2004a). Analysis of weighted networks. Physical Review E, 70(5), Article 056131. https://doi.org/10.1103/PhysRevE.70.056131
- Newman, M. E. (2004b). Fast algorithm for detecting community structure in networks. Physical Review E, 69(6), Article 066133. https://doi.org/10.1103/PhysRevE.69.066133
- Newman, M. E., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), Article 026113. https://doi.org/10.1103/PhysRevE.69.026113
- Rose, D., & Harrison, E. (2007). The European socio-economic classification: A new social class schema for comparative European research. European Societies, 9(3), 459–490. https://doi.org/10.1080/14616690701336518
- Rubin, D. B. (1976). Inference and missing data. Biometrika, 63(3), 581–592. https://doi.org/10.1093/biomet/63.3.581
- Sayer, A. (2010). Class and morality. In S. Hitlin & S. Vaisey (Eds.), Handbook of the sociology of morality (pp. 163–178). Springer. https://doi.org/10.1007/978-1-4419-6896-8_9
- Schmutte, I. M. (2014). Free to move? A network analytic approach for learning the limits to job mobility. Labour Economics, 29, 49–61. https://doi.org/10.1016/j.labeco.2014.05.003
- Shizuka, D., & Farine, D. R. (2016). Measuring the robustness of network community structure using assortativity. Animal Behaviour, 112, 237–246. https://doi.org/10.1016/j.anbehav.2015.12.007
- Soboleva, N. (2019). Gender attitudes and achievement motivation across Europe (The evidence of ESS data) [Research paper No. WP BRP 88/SOC/2019]. National Research University Higher School of Economics. https://wp.hse.ru/data/2019/10/18/1530677358/88SOC2019.pdf
- Stephens, N. M., Markus, H. R., & Phillips, L. T. (2014). Social class culture cycles: How three gateway contexts shape selves and fuel inequality. Annual Review of Psychology, 65, 611–634. https://doi.org/10.1146/annurev-psych-010213-115143
- Toubøl, J., & Larsen, A. G. (2017). Mapping the social class structure: From occupational mobility to social class categories using network analysis. Sociology, 51(6), 1257–1276. https://doi.org/10.1177/0038038517704819
- Toubøl, J., Larsen, A. G., & Jensen, C. S. (2013, May 21–26). A network analytical approach to the study of labour market mobility [Paper presentation]. 33rd Sunbelt Social Networks Conference of the International Network for Social Network Analysis (INSNA), University of Hamburg, Hamburg, Germany.
- Yastrebov, G. A. (2016). Sotsial’naia mobil’nost’ v sovetskoi i postsovetskoi Rossii: Novye kolichestvennye otsenki po materialam predstavitel’nykh voprosov 1994, 2002, 2006 i 2013 gg. Chast’ II [Social mobility in Soviet and post-Soviet Russia: A revision of existing estimates using representative surveys of 1994, 2002, 2006 and 2013. Part 2]. Universe of Russia, 25(2), 6–36.
Published
2023-12-27
How to Cite
Korotaev, S., & Gasiukova, E.
(2023).
Grouping of Occupations Based on Intragenerational Mobility.
Changing Societies & Personalities, 7(4), 71–92.
doi:10.15826/csp.2023.7.4.252
Issue
Section
Articles
