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WHAT THREE DIFFERENT AGRICULTURAL QUANTITATIVE SURVEYS TELL US ABOUT GENDER [Abstract ID: 1103-01]
This presentation uses the results from data mining three wheat focused datasets (CIMMYT Pakistan wheat dataset with total sample of 317, a CIMMYT Ethiopia wheat panel dataset with total sample 1978 and an IFPRI-Ethiopian pilot input voucher household dataset total sample of 591). Using descriptive statistics including estimation of mean, proportions, and production of charts along with t-tests and chi-square tests, we present results on the division of labor questions and sampling strategies. We find that two out of three samples are taken according to crops/yields, or climatic conditions and are not representative of the population. The surveys mostly have a low representation of youth and two out of three have a low representation of women. This makes comparisons by sex and age and across regions difficult. The presentation argues that in the era of big data we should be cognizant of how the way that we ask questions in surveys, who is involved in survey design, the response range offered and the sampling approach all have a bearing on how gender sensitive the results (and thus how visible women are in our datasets).