Hundreds of millions of people in the tropics need both wild harvests and other forms of economic development for their well-being
Bibliographic record
Abstract
Local access to "wild," common-pool terrestrial and aquatic resources is being diminished by global resource demand and large-scale conservation interventions. Many theories suggest the well-being of wild harvesters can be supported through transitions to other livelihoods, improved infrastructure, and market access. However, new theories argue that such benefits may not always occur because they are context dependent and vary across dimensions of well-being. We test these theories by comparing how wild harvesting and other livelihoods have been associated with food security and life satisfaction in different contexts across ∼10,800 households in the tropics. Wild harvests coincided with high well-being in remote, asset-poor, and less-transformed landscapes. Yet, overall, well-being increased with electrical infrastructure, proximity to cities, and household capitals. This provides large-scale confirmation of the context dependence of nature's contributions to people, and suggests a need to maintain local wild resource access while investing in equitable access to infrastructure, markets, and skills.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".