Gender and Transaction Costs in Use of Zero Grazing Net for Tsetse Fly and Trypanosomiasis Control in Stall Feeding Systems in Kenya
Bibliographic record
Abstract
Trypanosomiasis is a widespread constraint in livestock production, mixed farming and human health in Africa. Several technologies have been developed to ameliorate the effects of the disease but delivery of these technologies to farmers has been undertaken on trial and error basis without a proper strategy leading to more failure than success and wastage of scarce resources. The purpose of this paper was to carry out an analysis of transaction costs incurred in accessing and using insecticide treated net in tsetse and trypanosomiasis control among smallholder cattle farms in Busia County, Kenya. The study utilized cross–sectional survey design and was guided by the New Institutional Economics approach and utilized stratified and simple random sampling technique to get 211 respondents for the study. Data was collected by use of structured questionnaires and analyzed using descriptive and inferential statistics. Conjoint analysis results for zero grazing net showed that cost was the most important factor influencing farmers’ decision, accounting for 38.52% of the total while durability and availability each accounted for 25% and retreatability accounted for 10% of the decisions. Further t-test results showed that there were significant differences between men and women with respect to attribute scores (at 99 d.f. and alpha = 0.05%) suggesting that men and women face different transaction costs in accessing T&T control technologies. Therefore there is need for gender sensitive strategies in T&T technology design and dissemination. Tsetse fly and Trypanosomiasis control by use of low cost technologies such as insecticide treated zero grazing net should be promoted by government and other development partners. The net should be affordable, available at supply outlets close to farmers, long lasting and re-treatable for famers to take it up.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".