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Record W2079508856 · doi:10.1126/science.1102425

Bushmeat Hunting, Wildlife Declines, and Fish Supply in West Africa

2004· article· en· W2079508856 on OpenAlexaff
Justin S. Brashares, Peter Arcese, Moses Sam, Peter Coppolillo, A. R. E. Sinclair, Andrew Balmford

Bibliographic record

VenueScience · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBushmeatWildlifeWildlife tradeGeographyFisheryWildlife managementWildlife conservationNatural resource economicsEcologyEconomicsBiology

Abstract

fetched live from OpenAlex

The multibillion-dollar trade in bushmeat is among the most immediate threats to the persistence of tropical vertebrates, but our understanding of its underlying drivers and effects on human welfare is limited by a lack of empirical data. We used 30 years of data from Ghana to link mammal declines to the bushmeat trade and to spatial and temporal changes in the availability of fish. We show that years of poor fish supply coincided with increased hunting in nature reserves and sharp declines in biomass of 41 wildlife species. Local market data provide evidence of a direct link between fish supply and subsequent bushmeat demand in villages and show bushmeat's role as a dietary staple in the region. Our results emphasize the urgent need to develop cheap protein alternatives to bushmeat and to improve fisheries management by foreign and domestic fleets to avert extinctions of tropical wildlife.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.218
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations640
Published2004
Admission routes1
Has abstractyes

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