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Human Rights and Marginalized Groups

Human Rights and Marginalized Groups. Statistical measurement perspectives from South Africa. The present and future statistical opportunities and challenges will not be met effectively unless…. we change the way we think we organise and structure

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Human Rights and Marginalized Groups

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  1. Human Rights and Marginalized Groups Statistical measurement perspectives from South Africa

  2. The present and future statistical opportunities and challenges will not be met effectively unless… we change the way we think we organise and structure we do

  3. Why measure Human Rights? South Africa is a signatory of National Development Plan 2030; Sustainable Development Goals ; Agenda 2063 • Universal Declaration of Human Rights • International covenant on Economic Social and Cultural rights (signed 1994, ratified 2015) • International covenant on civil and political rights (signed 1994, ratified 1998) and additional protocols • At least 25 other aligned conventions and protocols

  4. Two important catalysts… • Move from survey based organisational structure to statistical themes. • Establish a special statistical unit that specifically looks at marginalised and vulnerable populations i.e. gender and vulnerable group (elderly, youth, disabled, children) statistics. Most NSO’s already have migration units.

  5. From Social Statistics to Governance (proposed) Criminal and civil justice system statistics Inclusion, equity and social cohesion statistics, focus: gender, elderly, youth and disabled Legitimacy, voice and equity, accountability, transparency and control of corruption statistics Leadership, direction, government effectiveness and performance statistics

  6. Human Rights Based Approach to data: Statistical Value Chain: GPS&J Survey Accountability Transparency Statistical Process: Governed by the Statistics Act no 6. of 1999; South African Statistical Quality Assurance Framework; Policies and Standards Input Output Privacy Need analysis Quality assuran-ce Design and plan Develop-ment and testing Disse-minate Editing and im-putation Evaluate Analyse Planning documents and stakeholder requirements Strategy Environ-ment Specifications and reports Review of literature Develop/ revise survey tools Monitor training Produce products for dissemination Run programs for analysis Lessons learnt Develop/ Revise Manual Editing system Research Stake-holders Survey tools, programs and systems Identify data items Testing and review of survey tools Monitor use of survey tools Mapping of data systems Media release Verification and validation Evaluate data quality and present to Survey operations Other projects Methodology Develop/ revise automated editing and imputation system Edited data Printing of questionnaires Survey instruments Advocacy and small group meetings Manage and attend to user enquiries Interpret data and write narrative report Resour-ces Develop metadata Processing systems specs. Stakeholder and internal review Releases and reports Finalise metadata HRC on data requirements ICESCR, DSD on CRPD, CGE on the AGDI Creation of derived variables Develop editing and imputation programs Participation Tabulation plan Archive document Evaluation reports Finalise outputs for analysis Stakeholder consultation: Govt, academics, civil society; Int. agencies Develop/ Revise project plans Develop programs for analysis Transparency Keep and update metadata

  7. Inclusion and Equity Disaggregation and self-identification • Sex, age, ethnicity, migration, disability, religion, civil status, income/Living standard measure. • Ethnicity include an option ‘’Other (specify)’’ which enables self-identification • The inclusion of sexual orientation and gender identity is still being researched. Caveat is sample size for what is currently still a statistical rare event.

  8. Measurement Imperatives

  9. Gender measurement: What to consider Is … male or female? • Sex: men (male) and women (female). • Gender: masculine or feminine. Gender choice can be due to sex – referring to biological differences between men and women • Concepts often treated as synonymous in surveys • Risks/poor practices: • Use of proxy respondents • Questions not asked, responses assumed based on names or physical appearance or voice • Using only two response categories and not making allowances for sex changes in the case of panel studies

  10. Age measurement and biological age Accuracy of biological age as per respondent’s records (CRVS) ABC Low levels of numeracy and literacy 123 Content and phrasing of the question Data collection methods (proxy versus self reporting and household record method)

  11. Age as important variable in grant provisioning Considerable provincial variations are notable. A third or more households in Limpopo, Eastern Cape and Norther Cape are dependent on Social Grants.

  12. Age Heaping

  13. Age heaping

  14. Addition of Date of Birth

  15. Conclusion: non- sampling errors and age measurement Birth registrations increasingly earlier – increased accuracy of age in population register The reporting of age in the QLFS data and the GHS data is overall very accurate The introduction of DoB question in addition to question on Age improved the accuracy of age measurement The appointment of permanent field staff and introduction of the record card (QLFS) had no significant impact on the accuracy of age reporting Proxy respondents increase age heaping, although not significantly Males and females tend to round ages to 0 and 5 equally

  16. Disability measurement: What to consider Conceptual framework to be used Functional Disability: Washington Group short set of questions used since 2009 Disability inequality index: ratios of disabled and non-disabled; index for males, females and total population

  17. Migration measurement: What to consider Were you born in South Africa? Are you a South African citizen?

  18. Dealing with Increased Measurement Demands Add questions or modules to existing instruments Create new survey instruments Extend age ranges Create new or add to existing registers & administrative data bases

  19. Create new survey instruments

  20. Governance, Public Safety and Justice Survey 2018/2019: Perceptions and Experience related to Inclusion and Equity Which of the following types of discrimination exists in South Africa? Sex or gender Age Have you personally experienced discrimination based on sex or gender during the past 12 months? Where did you experience the most recent discrimination based on sex/gender? Did you look for assistance or report the discrimination incident to anyone? Where did you report or seek assistance from?

  21. Other Human Rights Specific Questions • Perceptions about women, people’s sexual orientation and the disabled. • Perceptions and knowledge about human rights, the constitution and the bill of rights • Perceptions about the most import characteristics of a democracy as well as the extent to which it is practised in the country. • Access to civil and criminal justice • Extent to which democratic rights are exercised through voting.

  22. Access to Justice In the past two years which of the following disputes or problems did you experience? • Domestic violence • Conflict on child support, visitation and guardianship • Marriage or partnership • Etc. Follow-up questions with details about disputes/problems.

  23. Add to Existing Survey Instruments

  24. Example: Individual Asset Ownership (added to GHS 2017)

  25. Example South African DHS 2016 • Module on violence against women added • Women module conducted in isolation from other household members; creates opportunity for more sensitive questions such as violence • All women aged 15 and older living in partnerships

  26. Risks when adding questions/modules to existing survey instruments • Sample size may have been determined for another purpose • Increase respondent burden in existing survey • Flow and impact of preceding and successive questions on addition • Potential increase in time and costs

  27. Extend Age Ranges

  28. Example South African DHS Instead of females aged 15-49 and males 15-59; all individuals aged 15 years and older Applied to all three SADHS's (1998, 2003 and 2016) Risk: Levels of precision as a result of increasing the sample size or a potential proportional decrease in the traditionally eligible population of females aged 15-49 and males 15-59 that may have been made to accommodate the changes in the age cap. Costs: Estimated at 23,6% higher

  29. Create new or adjust existing registers/administrative data sets

  30. Examples • Non Financial census of municipalities based on registers kept at municipal level (add measurement of gender and disability - staff) • PERSAL (Govt wide financial and HR data system) Use self-reported disability for compliance; increase pressure to regularly update and increase completeness.

  31. Areas for further growth and improvement? • Establish a system to systematically guard research ethics • Increased participation at grass roots level in defining the measurement agenda, supplying data and participation in dissemination processes

  32. Thank You For more information about StatsSA projects: Isabella Schmidt isabelsc@statssa.gov.za

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