CHAPTER 5 Hunting for Justice An Indigenous Critique of the North American Model of Wildlife Conservation
Bibliographic record
Abstract
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.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".