Milano, 29 maggio 2015 GENDER INDICATORS for RURAL DEVELOPMENT PROGRAMS: THE WAY FORWARD of IAO-GENDER Angela Calvo University of Turin DISAFA (Departement of Agricultural, Forestry and Food Science) CISAO (Interdepartmental Centre for the Research and the Scientific Cooperation with the West Africa) CIRSDe (Interdisciplinary Centre of Gender Studies)

Indicator. This unknown object. THE CASE STUDY Context: An Agricultural Development Project to enforce the horticolture production in three Regions of Senegal Target: 4800 people, 3400 women (71%) Aim: Identify ‘some sound and operative’ gender indicators using national agency database The problems: 1. data availability at Regional level 2. Which gender indicators?

The indicator choice Nourishment Empowerment Economic An alike GHI (UI) aGII GQP. A new attempt: a gender ‘economically qualified’ presence

The Undernourishment Index (UI) vs. GHI Percentage of the population of each region with a BMI (Body Mass Index) <18.4

Adjusted Gender Inequality Index (aGII) Female and male participation in local institutions: low weight (low reliable data)

The GEQPAI, the GEQPRI and the GEQPUI gender Indicators economically qualified presence of women and men in agriculture (GEQPAI), in rural (GEQPRI) and in urban (GEQPUI) areas of the 3 target Regions Adult literacy Economically active population in agriculture/rural/urban areas Women and men responsible for resources in agriculture

Results: the cross reading. UI aGII

Index of Economically Qualified Presence of Women and Men in Agriculture, in Rural and Urban areas

Conclusions: numbers and policies Enforce the project efforts in the region where higher are the undernourishment and the gender disparities? …. Or focalize the actions where the economic disparities between men and women are more evident? …. And more: which indicators to monitor the work in progress?

Milan, 29 May 2015 GENDER INDICATORS for RURAL DEVELOPMENT PROGRAMS: THE WAY FORWARD of IAO-GENDER FROM THE THEORY TO THE FIELD Alice Centrone* University of Turin * DISAFA (Department of Agricultural, Forestry, and Food Sciences ) * CISAO (Interdepartmental Research Centre for Scientific Cooperation with West Africa)

Theory vs practice 2 key points: 1. The “best model” vs the data availability and the gender awareness 2. The goal project: improve the rural women’ entrepreneurship and technical skills. But which are the main aspects to be considered?

From national to regional and local. What happens in the field: the main problems a.statistical supply vs gender issues b.gender rural statistics in Senegal c.available data in the project context 1. The “best model” vs the data availability and the gender awareness

a. Statistical supply vs gender issues gender present only in the socio-demographic dimensions cross-cutting nature of gender necessity for clear and common tools and methodology 1. The “best model” vs the data availability and the gender awareness

b. Gender rural statistics in Senegal Lack of gender disaggregated data in the agricultural sector (mainly on produced quantities and exploited areas) Few information at Regional level Political implications Weakness of quantitative data vs qualitative surveys 1. The “best model” vs the data availability and the gender awareness

Only info on total hectares and number of women and men but ………….who are really the beneficiaries? 1. The “best model” vs the data availability and the gender awareness

It would be better to focus on the areas with less initial gender inequalities (as Thies and Fatick) by working directly on the economic empowerment aspects, which are the “easiest” and most efficient to pursue. 1. The “best model” vs the data availability and the gender awareness

 Age  Education  Fertility rate  Position within the management committees  Participation in technical trainings  Number of trained women  Number of women trainers 2. The goal project: improve the rural women’ entrepreneurship and technical skills

Conclusions Gender empowerment Gender policies Gender indicators

ACKNOWLEDGEMENTS We would like to thank the staff of DGCS, the past and present staff of the Local Technical Unit (UTL) of Dakar, the PAPSEN team and the national statistic office of Senegal (ANSD).