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WELI_IO

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WELI_IO

  1. 1. Better lives through livestock Adapting the Women’s Empowerment in Livestock Index (WELI) data collection tool to user demand Immaculate Omondi: i.omondi@cgiar.org Farha Deba Sufian: farha.deba.sufian@gmail.com Alessandra Galiè: a.galie@cgiar.org Nils Teufel: n.Teufel@cgiar.org 19 September, Nairobi, Kenya
  2. 2. 2 Overview of presentation - Women’s empowerment in livestock development: an introduction - Measuring the empowerment of women in livestock - Overview of WELI - Adapting WELI to Feedback from WELI Users
  3. 3. Women’s empowerment in livestock development
  4. 4. 4 Women’s empowerment in livestock 1 in 5 people in the world rely on livestock for their livelihoods (1.3 billion people) Women are the majority of poor livestock keepers…  Their empowerment: means for livestock development  SDG5: Women’s and girls’ empowerment as an end in itself Women’s empowerment as a means Women’s empowerment as an end
  5. 5. 5
  6. 6. Measuring the empowerment of women in livestock
  7. 7. 7 Measuring the empowerment of women in livestock to… • Measure whether livestock interventions enhance/hinder women’s empowerment • Study how livestock-specific interventions affect women's empowerment • Characterize women’s empowerment through livestock specific activities • Consider gender differences in roles/activities between livestock species • Identify sources of disempowerment facing the women participating in livestock production 2 tools in settings where livestock farming is the dominant form of livelihood Women’s Empowerment in Livestock Index (WELI) Women’s Empowerment in Livestock Business Index (WELBI)
  8. 8. 8 WELI: a standardized measure to assess the empowerment of women livestock producers • Developed by livestock and gender experts from ILRI and Emory University in 2014/2015 • Pilot tested in Tanzania, 2015 • Aligned to pro-WEAI with IFPRI, 2019 WELBI: a standardized measure to assess the empowerment of women livestock agri-preneurs • Constructed and aligned to pro-WEAI_VC, 2021 A short history of WELI and WELBI Women’s empowerment in the livestock business node of livestock value chains WELBI Women’s empowerment in the production node of the livestock sector WELI Women’s empowerment in the production node of crops mostly WEAI
  9. 9. Construction of the Index: comparing pro-WEAI and WELI 9 1 Autonomy in Income 2 Self-efficacy 3 Attitudes about IPV against women 4 Respect among household members 5 Input in household decisions about Production and Income 6 Ownership of land and other assets 7 Access to and decisions on financial services 8 Control over use of income 9 Work Balance 10 Visiting Important Locations 11 Group membership 12 Membership in influential groups Intrinsic Agency Instrumental Agency Collective Agency Pilot version of Pro-WEAI Additional Scenarios pertaining to livestock Additional options pertaining to livestock Update scenarios/options pertaining to livestock Input in household decisions with a Livestock focus WELI New Module 13 Indicators Weighted average score 3DE EMPOWERED if adequate in 75% of indicators
  10. 10. 10 • WELI has an elaborate list of livestock activities in decisions making modules: 24 vs 5 • WELI 3DE is estimated from 13 indicators vs 12 indicators • Empowerment can be assessed for more species and breed-type of livestock using WELI: 11 vs 6 • WELI integrates more livestock related scenarios/options in several modules (Autonomy, Domestic violence, Physical mobility etc.) • Decision making on livestock loops at most 3 times for: • Specie important to the household • Specie important to the woman • Project/target specie WELI vs Livestock-integrated Pro-WEAI
  11. 11. Adapting WELI to feedback from users
  12. 12. 12 Adapting to user feedback User Feedback • Lengthy interview • Issues with time module • High index values c Remove questions that DO NOT go into index calculation Recording Time by ACTIVITY vs 15 minute time slot Respondent Participation in decision making captured simply 3 main changes to WELI WELI- FullBare
  13. 13. 13 • HH roster dropped • Rows with items that do not go into the index • Some columns that do not go into the index • Questions asking for more than 1 decision maker • Time allocation consolidated • Intrahousehold relationships reviewed hence fewer non-response cases Major changes to WELI to produce the FullBare version
  14. 14. 14 Restructure in WELI-FB: MODULE G2 WELI WELI-FB • Livestock and productive activities decisions restructured in WELI-FB • Rows reduced to only activities/items that contribute to the index
  15. 15. 15 WELI • G3.10 restructured in WELI-FB WELI-FB Restructure in WELI-FB: MODULE G3
  16. 16. 16 WELI Time Module (by time slot) WELI-FB Time Module (by Activity) • Calculate time_work: minutes spent on work in 24 hours • Calculate time_childcare: minutes spent on childcare as secondary activity Restructure in WELI-FB: MODULE G4
  17. 17. 17 WELI WELI-FB • Relations expanded in WELI-FB Restructure in WELI-FB: MODULE G7
  18. 18. WELI Full bare validation
  19. 19. 19 1. Pilot study using WELI-FB questionnaire on 16 dual adult households (16 women and 16 women) in Ethiopia WELI-Full Bare Validations: pilot study ETHIOPIA Women Men Number of observations 16 16 3DE score 0.84 0.86 Disempowerment score (1 – 3DE) 0.16 0.14 % achieving empowerment 0.56 0.56 % not achieving empowerment 0.44 0.44 Mean 3DE score for not yet empowered 0.64 0.67 Mean disempowerment score (1 – 3DE) 0.36 0.33 Gender Parity Index (GPI) 0.95 % achieving gender parity 0.69 % not achieving gender parity 0.31 Average empowerment gap 0.16 WELI score 0.85
  20. 20. 20 2. Simulations using existing data on WELI to run WELI-FB syntax TANZANIA WELI WELI-FB Simulated Number of observations 210 210 WELI (3DE score) 0.86 0.86 Disempowerment score (1 – 3DE) 0.14 0.14 % achieving empowerment 62 62 % not achieving empowerment 38 38 Mean 3DE score for not yet empowered 0.63 0.63 Mean disempowerment score (1 – 3DE) for not yet empowered 0.37 0.37 Same results WELI-Full Bare Validation: simulations on existing data
  21. 21. 21 3. Length of the interviews Survey time comparison • Challenge: Recoded Survey time includes review time • Comparing Mean survey time across projects (restricting to survey duration less than 7 hours) • Full Bare records the lowest time on average WELI-Full Bare Validation: focus on length of interviews Estimate source Mean (hrs) Min (hrs) Max (hrs) Full WELI (Tanzania) 5.2 1.9 6.9 Full WELI (Ethiopia) 5.6 4.0 6.9 WELI – FB (Ethiopia) 4.8 2.0 6.8
  22. 22. WELI next steps
  23. 23. 23 Thoughts on next steps for (WELI-xs) Objective: Shorter interview (20-30 minutes) by reducing questions that form indicators (rather than no. of indicators that go into WELI) How: • Assess time required for questions and modules • Assess correlations between questions/items or activities within questions • Assess variation between questions/items or activities within questions • Theoretical background of these questions o Drop redundant questions/items or activities within questions (if any) • Analysis of 'candidate" indicators to dropped from WEAI o Variation/contribution to overall indicator and correlation with other indicators
  24. 24. 24 Challenges and doubts • High index values • Meaning of the indices vs general use of the results in light of ‘high index values’ observation o Interpreting absolute vs relative values of the index TANZANIA WELI Number of observations 210 WELI (3DE score) 0.86 Disempowerment score (1 – 3DE) 0.14 % achieving empowerment 62
  25. 25. 25 Questions for discussion • How others have dealt with the length of the surveys e.g. • Creating and validating shorter versions of the main tools • Using qualitative research in shortening the tools • Usefulness of additional questions that do not contribute to the index calculation • How others have dealt with ‘seemingly high’ index values
  26. 26. Acknowledgement • CGIAR GENDER Impact Platform Methods Module • Innovation Lab for Small- scale Irrigation (ILSSI) project
  27. 27. THANK YOU

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