Gender-Linked Dynamics and Sustainable Small Holder Poultry Value Chains in Makueni County, Kenya
Bibliographic record
Abstract
Understanding the gender-linked dynamics in the small holder poultry value chain is necessary for enabling sustainable agriculture and food systems. Small holder livestock production, including poultry keeping in sub-Saharan Africa (SSA), plays important socio-economic and food security roles in rural communities. Poultry production contributes to sustainable food systems as it supports nutrient cycling through feed, manure, and soils. A qualitative study utilized data from 18 focus group discussions (FGDs) and 22 in-depth interviews (IDIs) to interrogate the gender-linked dynamics in the value chain and inform interventions for sustainable food systems. The data were audio-recorded, transcribed, and coded into themes responding to the study question. The results highlight the gender-linked drivers, namely, the social and economic value placed on poultry, ownership, power positions, and decision making dynamics in production and management among small holder poultry value chain actors in Makueni County, Kenya. The study findings demonstrate the increasing economic and social value placed on poultry in households and communities. The study further discusses gender-disaggregated ownership and decision making in the poultry value chain, highlighting the need to engage all involved actors to develop sustainable food systems. In addition to the social and economic value of poultry to small holder farmers, it is necessary to factor in potential nutrition and environmental benefits. While small holder poultry production has the potential to contribute to sustainable food systems economically, nutritionally, and environmentally, this study found that more emphasis is placed on socio-economic value dimensions. Noteworthy is that in ownership and decision making, gender dynamics inform the role and position of the different actors in a sustainable small holder poultry value chain that is socio-economically, nutritionally, and environmentally sound.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".