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Record W2790496130 · doi:10.1126/sciadv.1701611

Undermining subsistence: Barren-ground caribou in a “tragedy of open access”

2018· article· en· W2790496130 on OpenAlexafffundabout
Brenda Parlee, John Sandlos, David Natcher

Bibliographic record

VenueScience Advances · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMemorial University of NewfoundlandUniversity of SaskatchewanUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaGwich'in Renewable Resources Board
KeywordsSubsistence agricultureIndigenousTragedy (event)Resource (disambiguation)GeographyEcologyArchaeologyBiologyAgricultureComputer scienceSociologySocial science

Abstract

fetched live from OpenAlex

) have declined over 70% in northern Canada over the last two decades in a cycle well understood by northern Indigenous peoples and scientists. However, as some herds reach critically low population levels, the impacts of human disturbance have become a major focus of debate in the north and elsewhere. A growing body of science and traditional knowledge research points to the adverse impacts of resource development; however, management efforts have been almost exclusively focused on controlling the subsistence harvest of northern Indigenous peoples. These efforts to control Indigenous harvesting parallel management practices during previous periods of caribou population decline (for example, 1950s) during which time governments also lacked evidence and appeared motivated by other values and interests in northern lands and resources. As mineral resource development advances in northern Canada and elsewhere, addressing this "science-policy gap" problem is critical to the sustainability of both caribou and 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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.002
Open science0.0020.002
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 head0.152
GPT teacher head0.538
Teacher spread0.386 · 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 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

Citations78
Published2018
Admission routes3
Has abstractyes

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