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Identifying gender inequalities and trade-offs in agriculture systems using RHoMIS

21/5/2019

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Dr Katie Tavenner
Katie is a gender research specialist and international development consultant. Her work connects gender, climate change, and environmental issues in farming systems. 
Scientists and development practitioners around the world are working with smallholder farmers to transform their agricultural practices to better adapt to, and even mitigate, climate change. The international development community has prioritized two strategies in this regard - increasing the sale of crop and livestock products through increased market participation (commercialization) and increasing the number of crop and livestock species on-farm (diversification).

​However, little is known as to the gendered impacts of these changes and specifically, whether these strategies may intensify inequalities between men and women. 
Luckily, RHoMIS has begun to fill this knowledge gap by collecting sex-disaggregated data from farmers across the globe on a variety of social and biophysical indicators. Using RHoMIS data from 2,859 households in Ethiopia, Kenya, and Tanzania, myself and a team of 18 co-authors were able to set out and investigate these impacts across different farming systems and household types. Our peer-reviewed article, “Intensifying Inequality? Gendered Trends in Commercializing and Diversifying Smallholder Farming Systems in East Africa” was published in Frontiers in Sustainable Food Systems (open access) earlier this year.  
I first had the opportunity to collaborate with Mark van Wijk and the RHoMIS community while I was a post-doctoral fellow in gender research at ILRI. When I started exploring the data, I was struck by how closely the relationships in the quantitative data resembled my qualitative interviews with dairy farmers in Kenya’s rift valley.

​One of the findings of my qualitative data was that married women had different opportunities to engage with commercial dairy marketing based on local gender norms, and were less likely to receive direct economic benefit from dairying compared to single women or men (read more here).  ​
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RHoMIS collects  gender-disaggregated data about rural households. (ILRI Flickr/PA)
These observations informed my thinking on how gender inequalities are multifaceted and contested within and outside of households and how the very categories of ‘men’ and ‘women’ can eclipse other important social dynamics. As I dived into the data, I was curious to see if RHoMIS would allow for additional nuance beyond the typical “head of household” sex-disaggregated analysis.

I was elated to find that RHoMIS collects additional gender-disaggregated data. When deciding on the unit for gender analysis, we chose to integrate the sex of the respondent and their marital status (e.g. married or single) to represent each RHoMIS farm household. We called this unit the “gender-respondent-household-typology”, which we divided into three categories: men respondents in coupled households, women respondents in coupled households, and women respondents in single households (in the data there were no male single households).

We decided on this aggregation for two reasons – first, to recognize that a full gender analysis is not possible without looking at the intersecting categories of social difference (intersectionality) that contribute to men’s and women’s experiences of inequalities. Second, to address the issue of gender respondent bias, which has been shown to play an important mediating factor in household survey response trends (more here). Using this approach, we were able to explore how the ‘female control indicator’ (which accounted for women’s control over incomes and foodstuffs produced through both on and off farm activities) was related to the household’s commercialization strategy, crop diversity, and livestock diversity, and how these relationships could differ by the gender and marital status of the respondent.
​After performing descriptive and inferential statistical analysis, our study results highlighted the trade-offs between farming practices and female control across gender-respondent-household typologies.

Female control scores were highest in farming systems with more land and more livestock. However, increasing commercialization resulted in an overall decline in female control across farming systems and gender-respondent-household typologies. In contrast, crop and livestock diversification were positively associated with female control across gender-respondent-household typologies.

​Interestingly, there were often statistically significant differences in levels of control reported between respondent categories, however, these differences were only in ‘degree’ since the overall trend reported by married men and women, and single women, were the same! 

In addition to the aggregated RHoMIS indicator data, we were able to ‘break open’ the indicators to analyze gendered control over specific crop and livestock products across farming systems. These analyses revealed women have far greater control over decisions related to consumption than decisions related to sales, although the gap between the two were less pronounced in lesser-valued livestock products (chickens, eggs). However, the analyses suggest that as sale of crops and livestock increase, female control over these areas could likely diminish, regardless of specific activity. 
In sum, our team was able to use RHoMIS to identify that on-farm strategies to adapt to and mitigate climate change have gendered tradeoffs and are associated with different patterns of female control.

​While our study showed that market commercialization in East Africa tends to weaken women’s control by focusing on sales rather than consumption decisions, diversification may allow women to have greater control through the inclusion of more “marginal” crops (vegetables, legumes) and livestock (chickens, eggs) in the farming system, thus creating a “social safeguard” against the potentially marginalizing effects of commercialization. 
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Women generally have far greater control over decisions related to consumption than decisions ​related to sales (ILRI Flickr/PA).
Reflecting on our experiences using this data, we believe RHoMIS can contribute towards cutting-edge gender research for agricultural development in several ways:
  • RHoMIS can be used to capture the negative, unintended consequences of development processes on gender relations.
  • By identifying the trade-offs between gender equity and farm strategies, RHoMIS can be used to inform social safeguards that could potentially minimize the negative consequences of commercialization on women’s livelihoods.
  • RHoMIS allows for maximizing data validity and tests of robustness across indicators by disaggregating gender data by respondent’s gender and household type as opposed to homogenizing “women” as an analytic category. This method of gender analysis ensures that crucial gendered trends and/or differences in reporting are not eclipsed or obfuscated by simplified metrics for comparing gender dynamics. 
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