The Importance of Bushmeat in Household Income as a Function of Distance from Protected Areas in the Western Serengeti Ecosystem, Tanzania
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
Bushmeat hunting is widespread in villages adjacent to protected areas in Western Serengeti. However, little information is available about the role of bushmeat income in the household economy as a function of distance from the protected area boundary, preventing the formulation of informed policy for regulating this illegal trade. This study was conducted in three villages in Western Serengeti at distances of 3 (closest), 27 (intermediate) and 58km (furthest) from the boundary of Serengeti National Park to assess the contribution of bushmeat to household income. The sample consists of 246 households of which 96 hunted or traded bushmeat, identified using snowball sampling through the aid of local informers. The average income earned from bushmeat was significantly higher for bushmeat traders than hunters. The contribution of bushmeat to household income was significantly higher in Robanda the village closest to the protected area boundary compared to Rwamkoma and Kowak, the more distant villages. A Heckman sample-selection model reveals that household participation in hunting and trading bushmeat was negatively associated with distance to the protected area boundary and with the household head being female. Household reliance on bushmeat income was negatively associated with age and gender of the household head and distance to the protected area boundary. Hence, efforts to reduce involvement in hunting, and trading bushmeat should target male-headed households close to the protected area boundary.
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.
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 | 0.000 |
| 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