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Record W2056514635 · doi:10.1017/s0032247406005481

Synergy of local ecological knowledge, community involvement and scientific study to develop marine wildlife areas in eastern Arctic Canada

2006· article· en· W2056514635 on OpenAlexaboutno aff
Mark L. Mallory, Alain J. Fontaine, Jason A. Akearok, Victoria H. Johnston

Bibliographic record

VenuePolar Record · 2006
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsWildlifeHabitatGeographyThe arcticGovernment (linguistics)ArcticLocal communityCitizen scienceEnvironmental planningEnvironmental resource managementEcologyEnvironmental protectionEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

The Canadian Arctic provides important habitat for millions of marine birds. Some key habitat sites for these have already been protected, but many others lack official protected status and remain vulnerable to various anthropogenic threats. The authors worked with the community of Qikiqtarjuaq, Nunavut, to create two new National Wildlife Areas that protect the colonies, and the nearby marine area, of approximately 500,000 birds during the breeding season. The process has taken two decades to complete, in part due to misunderstanding and mistrust of government on the part of aboriginal residents. In this paper the path that led to the creation of these sites is traced. This has included the approach adopted to collaborating with the local community, incorporating aboriginal (local) ecological knowledge, conducting scientific surveys while building local capacity for further scientific investigation, and finding a solution that addressed the disparate interests of the various stakeholders in this process.

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)0.012
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.005
Scholarly communication0.0040.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.327
Teacher spread0.284 · 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 designQualitative
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

Citations29
Published2006
Admission routes1
Has abstractyes

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