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Workshop on Occupational Data Collection: Usefulness and Limitations of ESeC Prototype in the French Context

This workshop aims to explore the relevance of the ESeC prototype for describing French society, with a focus on working conditions, cultural participation, and occupational mobility. It also examines the perception and understanding of the ESeC prototype among the general public. Alternative proposals for future socio-economic classifications are discussed.

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Workshop on Occupational Data Collection: Usefulness and Limitations of ESeC Prototype in the French Context

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  1. Workshop on the collection of occupational dataEurostat28-11-2009 Usefulness and limitations of ESeC prototype in the French context

  2. Plan 1. Is the ESeC prototype relevant for describing French society? Application to working conditions Application to cultural participation Application to occupational mobility 2. How is the prototype ESeC perceived by the general public? How easy is it to classify oneself in the prototype ESeC Do respondents understand the ESeC prototype ? 3. Proposals

  3. INTRODUCTION

  4. PARTIE 1Is the ESeC prototype relevant for describing French society ?

  5. Application to working conditions

  6. Working conditions Classifications « tested » : • national classification • ISCO - 2008 • prototype ESeC (full version)‏

  7. Working conditions The results • no classification is better than others • messages vary from one classification to another

  8. Working conditions Two ESeC classes are quiet heterogenous : • ESeC 6 (Higher grade blue collar workers)‏ some workers combine supervision and manual tasks while others are only responsible for supervision • ESeC 9 (Routine occupations)‏ Non skilledblue-collar workers and lower-grade white-collar workers are amalgated

  9. Application to cultural practices

  10. Cultural practices Results Full and simplified ESeC versions yield relatively similar results. The supervision dimension does not seem relevant for analysing cultural participation

  11. Application to occupational mobility

  12. Code ESec Nom Hommes Femmes 1 Higher salariat 17 17 2 Lower salariat 22 12 3 Higher grade white collar workers 35 19 4 Petit bourgeoisie or independants 18 20 5 Petit bourgeoisie or independants (domaine agricole)‏ 4 6 6 Higher grade blue collar workers 38 48 7 Lower grade white collar workers 33 21 8 Skilled workers 28 29 9 Semi- and unskilled workers 24 18 Changes in prototype ESeC among employees between 1998 and 2003

  13. Occupational mobility Results The ESeC prototype yields results that are fairly consistent with what we know of recent occupational mobility in France The very high mobility of men classified in ESeC 6 (supervisors) is a limitation The instability of this classe at an individual level makes it difficult to analysis long term phenomena (eg. health, property …)

  14. PARTIE 2How is the prototype ESeC perceived by the general public?

  15. How easy is it to classify oneself in the prototype ESeC?

  16. Do the respondents know how to classify their occupation in ESeC? The self-classification test used both versions  half the sample answered version A (for researchers )  half the sample answered version B (for general public)

  17. Do the respondents know how to classify their occupation in ESeC?

  18. PARTIE 2 Alternative proposals to ESeC prototype

  19. Proposal 1 :The future European socio-economic classification could be based on three dimensions : 1) skill level 2) skill specialisation 3) status

  20. Proposal 2 : The future European socio-economic classification could be built from the second aggregation level of ISCO-08 by combining sub-major groups

  21. Proposal 3 : Eurostat classification could comprise two aggregated levels, the second level (available in the LFS, SRCV) offering greater flexibility for rearrangements than the first, especially for researchers. For instance, a classification similar to the prototype ESeC could be built from the second level.

  22. First implication : For skill (level-specialisation) reasons sub major groups could be rearranged (especially SMG 41 to 96) Second implication : The aggregated classification does not include a class entirely composed of supervisors

  23. 7 groups composed mainly of employees 2 groups composed of self-employed workers Business executives and managers Business owners, craft workers and retailers Intellectual and scientific occupations(i.e.management-level workers in public-interest services)‏ Farmers Intermediate occupations Skilled lower-grade white-collar workers Skilled blue-collar workers Low-skilled white-collar workers Low-skilled blue-collar workers An example of classification based on ISCO-08 two-digits and core variables

  24. 7 groups composed mainly of employees 2 groups composed of self-employed 11 12 13 24 11 12 13 14 24 61 6251 52 14 71 72 73 74 75 81 83 91 95 1124 01 21 22 23 25 26 31 32 33 14 34 35 02 61 62 63 92 41 43 44 53 54 03 61 62 81 71 72 73 74 75 51 52 42 91 95 82 83 91 92 93 94 96 An example based on ISCO-08 two-digits and core variables

  25. But this is just an example ! The weight to be assigned to each dimension (skill level, sector, status) should be discussed among NSI and with users and of course the classification should be validated using harmonised data sources

  26. Thanks you for your attention

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