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Record W4399180324 · doi:10.1515/9781800732858-006

CHAPTER 5 Hunting for Justice An Indigenous Critique of the North American Model of Wildlife Conservation

2022· book-chapter· en· W4399180324 on OpenAlexaboutno aff
Lauren Eichler, David Baumeister

Bibliographic record

VenueBerghahn Books · 2022
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousWildlifeEnvironmental ethicsGeographyWildlife conservationWildlife managementEconomic JusticeEnvironmental planningPolitical scienceSociologyEnvironmental resource managementEcologyEnvironmental scienceBiologyPhilosophyLaw

Abstract

fetched live from OpenAlex

The North American Model of Wildlife Conservation (hereafter NAM) is an umbrella term for a set of conservation policies and principles that has in recent decades become the prevailing doctrine within US and Canadian wildlife protection and management agencies.According to a 2012 technical review published by the Wildlife Society and the Boone and Crockett Club, the NAM "has led to the form, function, and successes of wildlife conservation and management in the United States and Canada" (Organ et al. 2012: viii).As the theoretical underpinning for policies aimed at ensuring equal access to natural resources for all citizens, the NAM is framed as a tool for "democratic engagement in the conservation process" (3).The model's core principles reflect this agenda.They include the following:(1) Wildlife resources are a public trust.(2) Markets for game are eliminated.(3) Allocation of wildlife is by law.(4) Wildlife can be killed only for a legitimate purpose.(5) Wildlife is considered an international resource.(6) Science is the proper tool to discharge wildlife policy.(7) Democracy of hunting is standard.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.357
Teacher spread0.289 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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