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Challenges in measuring gender and minorities

ECE/CES/GE.30/2006/21. Challenges in measuring gender and minorities. Govinda Dahal (presented by E.Bisogno) UNECE Work Session on Gender Statistics, 11-13 September 2006. Minority status: what is it?. Very complex, country specific

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Challenges in measuring gender and minorities

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  1. ECE/CES/GE.30/2006/21 Challenges in measuring gender and minorities Govinda Dahal (presented by E.Bisogno) UNECE Work Session on Gender Statistics, 11-13 September 2006

  2. Minority status: what is it? • Very complex, country specific • Different dimensions (ethnicity, race, religion, social groups, sexual orientation, disability status, etc.) • A choice is made here: ethno-cultural characteristics (often in relation with immigrant background)

  3. The policy issues • Double disadvantage/discrimination of women: as minority members + as women • Gender roles as key issue to hinder or to facilitate integration of minority communities

  4. The statistical issues • Data gaps • Different criteria to identify minority groups • Data quality

  5. 1. Data gaps • Asking about ethnicity or related aspects can be very sensitive. • For example: • 2000 Census Round, 40% of ECE countries did not ask about ethnicity. • Little availability of MDG indicators by ethnicity • As a consequence, few data available, especially in key areas for gender analysis

  6. 2. Different definitions • Subjective criteria: ethnic affiliation • The ‘best’ approach, if based on self-declaration • Based on individual perception, it can change • Objective approach: foreign background • Especially valid to identify immigrant communities, including descendants of migrants (based on place of birth and place of birth of parents)

  7. 3. Data quality • Ethnic group can be a stigma • Statistical problems deriving from small size of ethnic minorities • Administrative data, when available, can have accuracy problems

  8. Some recommendations • Increase data availability • Select the best criteria according to national context • Data quality is crucial

  9. 1. Increase data availability • Mainstream ‘minorities’ in all statistical production, especially in gender relevant areas. • Population census: what are the plans for next round? • Household surveys: are the same questions used across the board? • Administrative sources: very important, especially when an objective approach is used

  10. 2. Select the best criteria • There is no ‘best’ criteria. • Every country should select the most appropriate according to the context • However, once selected, it should be applied consistently across the board

  11. 3. Address data quality • Quality is an issue, especially when the subjective approach is selected • Confidentiality must be assured and respondents must be aware of it • Self declaration must be ensured: open-ended questions are better, multiple options allowed • Survey sampling frame to include minority groups • Sample size to ensure minority groups, over-sampling may be necessary

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