Women's Empowerment: A Key Mediating Factor between Cotton Cropping and Food Insecurity in Western Burkina Faso
Bibliographic record
Abstract
We examined associations between cotton cropping, women's empowerment, and household food insecurity in Burkina Faso. A cross-sectional study was conducted during the 2012 pre-harvest period. Socioeconomic characteristics and agricultural production data were collected using a questionnaire. The Household Food Insecurity Access Scale (HFIAS) questionnaire was used to assess household food insecurity. Four villages of western Burkina Faso were selected for the study. In total, 275 farmer's households, who had at least one child between the age of 6 and 59 months, participated in the survey. Food insecurity affected 67% of households. HFIAS score was negatively correlated with the Household Dietary Diversity Score (HDDS) (r = - 0.40, P = 0.000006). Cotton cropping was not directly associated with the HFIAS score, while women's workload (positively) and income-generating activities (negatively) were. Interestingly, the only village where women could own cotton fields was negatively associated with the HFIAS score. An intensive cotton production was positively associated with the amount of time women spent fetching water and was tendentiously associated with women's working time in cotton fields. Finally, the size of cotton farms was positively associated with the practice of petty trading. The relationships between cash cropping, women's daily activities, and food insecurity are dynamic, behaviour related, and should be targeted for appropriate behaviour change intervention in order to alleviate food insecurity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".