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Engendering Labour Statistics

This article explores the gender bias in collecting, processing, and disseminating employment statistics. It examines biases in data collection, definitions, responses, enumerators, and content. Suggestions for improvement are discussed.

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Engendering Labour Statistics

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  1. Engendering Labour Statistics UNECE Statistical Division

  2. Segregation

  3. Activity rate Unemployment Rate

  4. Employment Rate

  5. Labour Force Surveys, Census, Surveys Enterprise surveys, LFS, Census LFS, Census, Registers

  6. Engendering Labour Statistics How can we make the process of collecting, processing and disseminating employment statistics more gender sensitive?

  7. Engendering Labour Statistics Where is the gender bias? • Man-biased data collection (question wording) • Inadequate definitions and concepts • Gender-biased responses • Gender-biased enumerators • Gender-blind content of the data collection

  8. Engendering Labour Statistics Question wording • Formally there is a clear distinction between employed and non employed population • ILO definition: a person is currently employed if he/she has worked at least one hour the week previous the survey • Work: for income (cash or kind) or unpaid production of goods

  9. Engendering Labour Statistics Question wording Prior 1994, US Labour Force Survey (LFS): “What were you doing most of last week—working, keeping house, or something else?” For women who primarily kept house but also did some paid work, this question appears to have led to some underreporting of work Now, US LFS: “Last week, did you do any work for pay or profit?” Following the redesign, the survey found an increase in the number of workers, primarily women, who usually worked fewer than 10 hours per week

  10. Engendering Labour Statistics Question wording Can the LFS questions be improved to include all women and men who do work according to the ILO definition? Do the current questions capture persons who have “atypical jobs”?

  11. Engendering Labour Statistics Question wording Concepts should be operationalized in a way that respondents can understand it. What does work mean? What does child care mean? Cognitive testing, focus groups help to make sure that the concepts used are interpreted correctly

  12. Engendering Labour Statistics Concepts and definitions • Women’s work tend to be more heterogeneous than men’s work, but standard classifications are more one-dimensional • Some unit of analysis hide the individual (and therefore the gender) dimension • household, farm, economic unit

  13. Engendering Labour Statistics Gender-biased responses • Male respondents may fail to report women • Respondents may not understand the content of the questionnaire • Respondent give wrong answers to meet social norms

  14. Engendering Labour Statistics Meeting social norms: US Survey Example The following questions and results were obtained in an American survey % 'Yes' Have you ever heard the word AFROHELIA? (no such word!) 8 Have you ever heard of the famous writer, John Woodson? (no such writer!) Have you ever heard of the Midwestern Life Magazine? (no such magazine!) Do you recall that, as a good citizen you voted last December in the special election for your state representative? (no election!) 16 25 33 Have you ever heard of the Taft-Pepper Bill concerning veteran's housing (no such bill!) 53 Sometimes this type of bias is called prestige error

  15. Engendering Labour Statistics Gender-biased enumerators • Enumerators may introduce his/her personal view (norm) in the interview • Poor training • Social pressure • Lack of interest • Enumerators may establish poor relationship • Not gender-correct language • Body language

  16. Engendering Labour Statistics Enumerator-bias: Example Australian Survey Average number of sex partners reported • By women who were watched as they filled in their survey answers: 2.6; • By women who knew they were completely anonymous: 3.4; • By women who thought they were attached to a lie detector: 4.4 Sydney Morning Herald, August 31, 2003

  17. Engendering Labour Statistics Gender-blind content What are the gender issues in employment? ……….Next activity………….

  18. Thank you !

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