Bushmeat and livelihoods : wildlife management and poverty reduction
Bibliographic record
Abstract
Contributors. Preface. Introduction (David Brown and Glyn Davies). Part 1. Bushmeat: Markets and Households (Glyn Davies and John G. Robinson). 1. Hunting and trapping in Gola forests, south-eastern Sierra Leone: Bushmeat from farm, fallow and forest (Glyn Davies, Bjorn Schulte-Herbruggen, Noelle F. Kumpel, and Samantha Mendelson). 2. Livelihoods and sustainability in a bushmeat commodity chain in Ghana (Guy Cowlishaw, Samantha Mendelson, and J. Marcus Rowcliffe). 3. Bushmeat markets - white elephants or red herrings? (John E. Fa). 4. Cameroon: from free gift to valued commodity. The bushmeat commodity chain around the Dja Reserve (Hilary Solly). 5. Determinants of bushmeat consumption and trade in continental Equatorial Guinea: an urban-rural comparison (Noelle F. Kumpel, Tamsyn East, Nick Keylock, J. Marcus Rowcliffe, Guy Cowlinshaw, and E.J. Milner-Gulland). 6. Livelihoods, hunting and the game meat trade in northern Zambia (Taylor Brown and Stuart A. Marks). Part 2: Institutional contexts (E.J. Milner-Gulland). 7. Is the best the enemy of the good? Institutional and livelihoods perspectives on bushmeat harvesting and trade - some issues and challenges (David Brown). 8. Bushmeat, wildlife management, and good governance: rights and institutional arrangements in Namibia's community based natural resources management programme (Christopher Vaughan and Andrew Long). 9. Wildlife management in a logging concession in Northern Congo: can livelihoods be maintained through sustainable hunting? (John R. Poulsen, Connie J. Clark, and Germain A. Mavah). 10. Institutional challenges to sustainable bushmeat management in Central Africa (Andrew Hurst). Part 3. Extra-Sectoral Influences and Models (Jo Elliott). 11. Can wildlife and agriculture coexist outside protected areas in Africa? A hopeful model and a case study in Zambia (Dale M. Lewis). 12. Food for thought for the bushmeat trade: lessons from the commercialisation of plant NTFPs (Elaine Marshall, Kathrin Schreckenberg, Adrian Newton, Dirk Willem te Velde, Jonathan Rushton, Fabrice Edouard, Catarina Illsley, and Eric Arancibia). 13. Bushmeat, forestry and livelihoods: exploring the coverage in PRSPs (Neil M. Bird and Chris S. Dickson). 14. The Beverly and Qamanirjuaq Caribou Management Board (BQCMB): blending knowledge, people and practice for barren-ground caribou conservation in Northern Canada (Ross C. Thompson). Part 4: Regional perspectives (Glyn Davies and Ruth Whitten). 15. Hunting, wildlife trade and wildlife consumption patterns in Asia (Elizabeth L. Bennett). References. Index.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.178 | 0.057 |
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".