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Record W4388510749 · doi:10.1017/9781009006828.022

Buffalo Hunting: From a Commodity to a High-Value Game Species

2023· book-chapter· en· W4388510749 on OpenAlexaff
Philippe Chardonnet, Russell Taylor, William‐Georges Crosmary, Serge Patrick Tadjo, Fredrick Ambwene Ligate, Rolf D. Baldus, Ludwig Siege, Daniel Cornélis

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMinistère des Ressources naturelles et des Forêts
Fundersnot available
KeywordsTrophyWildlifeCITESGeographyNational parkGame reserveWildlife tradeResource (disambiguation)PoachingCommodityFrontierTanzaniaLivestockBusinessAgroforestryFisheryEnvironmental planningEcologyForestryBiology

Abstract

fetched live from OpenAlex

Whether practiced legally or illegally, formally or informally, hunting buffalo for meat occurs broadly across African cultures. Nearly all buffalo parts are prized in addition to the meat. Buffalo are also hunted for traditional medicine, social positioning, mystical reasons and in retaliation for causing damage to people and crops. The buffalo is a major game for the hunting industry in every country, but the reasons vary from place to place. In South Africa, buffalo is the first income-generating game despite being the least hunted of all important game. In Tanzania, despite a trophy fee that is lower than that of other species, buffalo is the top tax-earning game because it is the most hunted among the important game. As duly gazetted protected areas, hunting areas are contributing internationally to the global network of conservation areas. They more than double the land area that is used for wildlife conservation in sub-Saharan Africa. Acting as buffer zones of national parks and as corridors between national parks, hunting areas are the last frontier of the African buffalo outside national parks. In South Africa, where all buffalo are fenced and buffalo hunting occurs behind fences, the buffalo is subject to genetic manipulation to enlarge trophy horns and produce disease-free herds. While ‘clean buffalo’ widely contributed to expanding the land dedicated to wildlife conservation in a beef-exporting country, ‘augmented buffalo’ remain a matter of concern for the long-term conservation of the taxon. Several non-African countries imposed bans on importing hunting trophies of CITES-listed species from Africa, leading to a drop in the hunting market. The bans are having two impacts on buffalo: (i) although not CITES-listed, the buffalo is a collateral victim of the bans because many abandoned hunting areas are exposed to poaching and habitat conversion; and (ii) unintentionally, the bans are lifting the value of buffalo as a leading flagship game in an attempt to compensate for the loss of CITES-listed game. Hence, once a commodity game, the buffalo is turning into a high-value game.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.001

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.

Opus teacher head0.025
GPT teacher head0.186
Teacher spread0.161 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

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