A Gendered Value Chain Analysis of Post Harvest Losses in the Barotse

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GAF6 – Bangkok, Thailand (August 4, 2016) Alexander Kaminski, Alexander Kefi , Steven M Cole, Kate Longley, Chifuniro Somanje , Pamela Marinda , Ansen Ward, Alexander Chilala , and Gethings Chisule A Gendered Value Chain Analysis of Post Harvest Losses in the Barotse Floodplain, Zambia

Research project site :

Research project site Lake Chilwa

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Research Question One What is the gendered nature of post-harvest losses (biophysical and economic) in the value chain?

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What are the social and gender constraints to post-harvest losses and does gender inequality contribute to losses? The “social” development challenge

Types of post-harvest losses (PHL):

Types of post-harvest l osses (PHL)

PHL in sub-Saharan Africa:

PHL in sub-Saharan Africa The fisheries contribution to GDP in Africa is around 1.26% The economic and biodiversity value of fisheries is important to 200 million people in SSA ( NORAD, 2009) Women make up 27.3% of the people engaged in fisheries-related activities in Africa 3.6% of fishers and 60% of processors/traders are women (de Graaf & Garibaldi, 2014) It is believed that PHL within small-scale fisheries in Africa are among the highest for all the food commodities ( Morrisey 1988; Hodges et al. 2011 ) Total losses are about 5% in SSA and a further 20-30% are due to q uality losses ( FAO, 1996; Akande & Diei-Ouadi , 2010 )

The Barotse Floodplain fishery :

The Barotse Floodplain fishery Poorest region in Zambia – 80.4% of people living in poverty (CSO, 2012) Migratory fishing camps where daily consumption of fish is five times the national average ( Turpie et al ., 1999) Capture fisheries contribute over 70% to mean household income in the floodplain About 75% of fishers are men and about 25% are women ( Turpie et al ., 1999 ) and more than 80% of traders are women (Longley et al., 2016) Gender inequalities are pervasive in Zambia Norms and power relations create gender inequalities in access to and benefits derived from the fishery ( Rajaratnam et al., 2016a, 2016b; Cole et al., 2015) I llegal fishing contributes to dwindling fish stocks (Kolding and van Zwietan , 2014; Turpie et al ., 1999; Tweddle et al ., 2015 )

Research methodology:

Research methodology BASELINE INSTRUMENTS Exploratory Fish Loss Assessment Method (EFLAM) Quantitative Fish Loss Assessment Method (QLAM) Gross Margins Analysis (GMA) Women’s Empowerment in Fisheries Index (WEFI) RESEARCH APPROACHES Participatory Action Research (PAR) with women and men testing the post-harvest fish processing technologies Practical Needs Approach (PNA) to ensure women’s/men’s practical needs are accommodated Gender Transformative Approach (GTA) to challenge and address the norms/power relations that cause gender inequalities in the fishery value chain

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EFLAM/QLAM Women’s empowerment Losses Profitability Designing and testing technologies and social change interventions to reduce PHL Participatory action research Gender Transformative approach GMA WEFI

Exploratory Fish Loss Assessment method (EFLAM):

Exploratory Fish Loss Assessment method (EFLAM) Focus group discussions in six fishing camps the research project is operating in Qualitative scoping about losses (for whom, how, why, where, when, etc.)

Quantitative Loss Assessment Method:

Quantitative Loss Assessment Method Sample of 176 people (33% women , 67% men ) from six fishing camps Given some fishers also processed fish [28.3% of fishers (all men )], total sample = 206, with: Fishers = 106 (2% women , 98% men ) Processors = 60 (40% women , 60% men ) Traders = 40 (80% women , 20% men ) Measured physical loss and reasons for loss, by sex and node Measured economic loss and reasons for loss, by sex and node

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Women: n=2 Men: n=104 Women: n=32 Men: n=8 Women: n=24 Men: n=36

15.09% of fishers experienced loss primarily due to spoilage (53%) 44.83% of processors (63% of women, 32% of men: p-value = 0.0228) experienced loss primarily due to breakage (82% of men, 47% of women) and over processing (33% of women, 9% of men) 30% of traders (35% of women, 13% of men: p = 0.2379) experienced loss due to breakage (64% of women, 100% of men) and spoilage (36% of women) :

15.09 % of fishers experienced loss primarily due to spoilage (53%) 44.83 % of processors ( 63% of women, 32% of men: p-value = 0.0228) experienced loss primarily due to breakage (82% of men, 47% of women) and over processing (33% of women, 9% of men) 30 % of traders (35% of women, 13% of men: p = 0.2379 ) experienced loss due to breakage (64% of women, 100% of men) and spoilage (36% of women)

Fishers experienced loss primarily due to spoilage (34%) and market forces* (55%) Processors experienced loss primarily due to breakage (58% of women, 55% of men) and market forces (42% of women, 36% of men) Traders experienced loss due to breakage (25% of men, 17% of women), spoilage (42% of women, 25% of men), and market forces (50% of men, 42% of women):

Fishers experienced loss primarily due to spoilage (34%) and market forces* (55%) Processors experienced loss primarily due to breakage (58% of women, 55% of men) and market forces (42% of women, 36% of men) Traders experienced loss due to breakage (25% of men, 17% of women), spoilage (42% of women, 25% of men), and market forces (50% of men, 42% of women) *Size variation, high supply, price variation

Gross Margins Analysis:

Gross Margins Analysis Sample of 239 people (33% women , 67% men ) from fishing camps and in town Fishers = 113 (100% men ) Processors = 50 (70% women , 30% men ) Traders = 76 (56% women , 44% men ) Gross margins analysis measures the difference between revenue and costs of goods sold and expressed as a percentage indicating profitability of an enterprise

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Women processors incur higher variable costs on average and receive lower prices for fish Women traders receive better prices but incur much lower variable costs. Men traders have very high variable cost

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100% men 70% women 56% women

WEFI:

WEFI Adapted from the women’s empowerment in agriculture index (WEAI) (IFPRI, 2012) Sample of 151 people (39% women , 61% men ) Measured access to assets, decision-making powers, individual leadership capabilities, gender attitudes and allocation of time Primary reason women are in the fishing camps: 73% to trade fish 15% to process fish 7% to fish 5% to do something else Primary reason men are in the fishing camps: 90% to fish 9 % to trade fish 1% to do something else

Access to assets:

Access to assets A larger percentage of women’s households own locally-produced fishing equipment (e.g., fishing baskets) compared to men’s ( 46% versus 30% ) A larger percentage of men’s households own externally-produced fishing equipment (e.g., seine nets, hooks) compared to women’s ( 86% versus 34% ) Importantly , 0% of women own such gears themselves, while 62% of men do No women make their own decisions to sell, rent/give away or purchase new externally-produced fishing gears, while majority of men do Similar results for women and men regarding processing and trading

Individual leadership in the camps:

Individual leadership i n the camps 51% of women felt very comfortable speaking in public to help decide on projects or issues affecting the fishing camp, compared to 83% of men . 56% of women felt very comfortable speaking in public to protest the use of illegal fishing gears or activities, compared to 87% of men .

Gender attitudes:

Gender attitudes Women have more gender equal attitudes than men (p-value = 0.0019) A greater percentage of men compared to women feel that women should not get involved in fishing and women should primarily be the ones who clean and process fish More men than women feel that they should primarily be the ones who control the earnings obtained from the sale of fish A greater percentage of men compared to women felt men should primarily be the ones who transport fish to a market for sale Women and men almost equally believe that women should primarily be the ones who prepare meals (including fish) Gender Attitudes Mean Women 19.98* Men 18.11 *Perfect gender equal attitude score = 24, perfect gender unequal attitude score = 8

Conclusions:

Conclusions Women face higher physical and economic losses than men Women incur smaller gross margins in processing node A greater percentage of men make individual decisions on many fishing-, processing-, and trading-related processes Gender attitudes about women’s and men’s involvement in key activities in (and outside) the fishery value chain and their allocation of time devoted to paid and unpaid (e.g., home-based) activities may influence women’ abilities (in particular) to process higher-quality fish with minimal losses

Drivers of PHL:

Drivers of PHL Complex no doubt Poverty and marginalization, lack of access to improved technologies and markets, climate change, etc. BUT also… Women’s access to resources, lack of individual decision-making powers, socially-assigned roles and gender attitudes, and time allocation (especially carrying out unpaid tasks)

How the project is utilizing these results:

How the project is utilizing these results Social and gender analysis to highlight harmful norms, behaviors and power relations in a PHL context Design and test innovations that address that cause gender inequalities and prohibit women from processing higher quality fish Reduced gender gaps Greater adoption and utilization of technologies Improved gender relations More sustained development impact for all Research output Outcomes Impact Figure: Gender transformative impact pathway to change

Participatory action research:

Participatory action r esearch PAR on Post Harvest Fish Losses PAR on Solar Drier PAR on gender roles

PHL-reducing technologies:

PHL-reducing technologies

Using PAR to implement technologies:

Using PAR to implement technologies

Gender transformative communication tool:

Gender transformative c ommunication t ool

Key insights:

Key insights Post-harvest fish losses literature lacks gendered analyses Gender norms and power relations influence how, when, where fish get processed and as a corollary contribute to post-harvest losses in the value chain, and especially for women occupying the processing node Gender transformative approaches and post-harvest fish processing technologies should be tested/promoted together to address both the technical and social issues that lead to PHL PAR can be a vehicle for implementation by building ownership of the research and developing capacities

Acknowledgments:

Acknowledgments The research project is funded by IDRC and ACIAR under the Cultivate Africa’s Future ( CultiAF ) fund The Zambia component of the research project is being implemented by the Department of Fisheries, University of Zambia, WorldFish, and NoNo Enterprises

Thank You!:

Thank You!

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