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Record W1597888303 · doi:10.11575/prism/10151

Wildlife Conservation in the North: Historic Approaches and their Consequences; Seeking Insights for Contemporary Resource Management

2008· article· en· W1597888303 on OpenAlexaffabout
John Sandlos

Bibliographic record

VenueOpen MIND · 2008
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWildlifeWildlife conservationWildlife managementBureaucracyNorth American Model of Wildlife ConservationEnvironmental ethicsPoliticsEnvironmental resource managementResource management (computing)GeographyEnvironmental planningPower (physics)Political scienceEcologyLawEconomics

Abstract

fetched live from OpenAlex

Recent studies in the field of Canadian environmental history have suggested that early state wildlife conservation programs in northern Canada were closely tied to broader efforts to colonize the social and economic lives of the region's Aboriginal people.Although it is tempting to draw a sharp distinction between the "bad old days" of autocratic conservation and the more inclusive approaches of the enlightened present such as co-management and the incorporation of traditional ecological knowledge (TEK) into wildlife management decision-making, this paper will argue that many conflicts associated with the older colonial conservation regime have survived to the present day.Recent anthropological literature has suggested that traditional environmental knowledge is often marginalized in wildlife decision making bodies when juxtaposed with scientific expertise or bureaucratic priorities.Aboriginal people may now be recognized as formal participants in the management of wildlife and protected areas, but this tentative shift in political power represents an incomplete attempt to decolonize wildlife management practices in the North.The paper concludes with policy recommendations that might further apportion power over northern wildlife and protected areas to Aboriginal people.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.275
GPT teacher head0.351
Teacher spread0.076 · 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 designNot applicable
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

Citations2
Published2008
Admission routes2
Has abstractyes

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