Gender differences in willingness to pay for capital-intensive agricultural technologies: the case of fish solar tent dryers in Malawi
Bibliographic record
Abstract
Gender differences in fish processors’ willingness to pay for a group-owned fish solar tent dryer (FSTD) are being assessed by using the double hurdle model. Willingness to pay (WTP) responses from 382 randomly selected fish processors were elicited through a bidding game in a contingent valuation method. The findings show that the average probability that fish processors will be willing to pay was 74% (76% for females and 72% for males). Furthermore, the average level of WTP was US$29.45 (US$26.46 for females and US$33.51 for males). Females have a lower level of WTP than men because of their low endowment with assets that can assist them such as education, access to markets and productive assets. In view of these findings, the paper concludes that female fish processors have a higher probability of being willing to pay than male fish processors, but the levels of WTP are lower for female processors. The study suggests that when organising the community into cooperatives is possible, WTP for capital-intensive technologies can be assessed as contributions of individuals to the total cost of the technologies although the common property characteristic is suspected to lower the level of willingness to pay.
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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 | 0.000 | 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 | 0.000 |
| 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".