Forests and cycles of agrarian sustenance: time-to-event analysis of ecosystem provisioning services and seasonal food insecurity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In Savanna ecosystems, cycles of sustenance include periods of food abundance and deficits. In rain-fed agricultural systems, forests are a vital food source that helps households close this cycle. This paper uses cross-sectional data to explore the association between provisioning ecosystem services and timing to food insecurity in forest fringe communities (N = 500). The time to food insecurity analysis revealed a significant difference in the onset of food insecurity among households with varying levels of access to forest provisioning services. Households with access to more than four forest products experienced a slower timing to seasonal insecurity. In contrast, those with access to less than two experienced a faster seasonal food insecurity onset. The time-to-event analysis further showed that as the number of provisioning services households access increased, households experienced delayed seasonal food insecurity. Access to multiple services allows households to combine them to provide nutritious food during lean seasons when food supplies and income are depleted. Our findings suggest that economic and agronomic factors, including wealth, farm size and number of farms, mediate the onset of food insecurity among smallholders. Our findings reinforce the need for a rights-based approach to forest management that prioritizes local stewardship against forest enclosures.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it