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Record W2408857856 · doi:10.14430/arctic4562

Wild Resources, Harvest Data and Food Security in Nunavut’s Qikiqtaaluk Region: A Diachronic Analysis + Online Supplementary Appendix Table S1 (See Article Tools)

2016· article· en· W2408857856 on OpenAlexafffundvenueabout
George W. Wenzel, Jessica Dolan, Chloë Brown

Bibliographic record

VenueARCTIC · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMcGill UniversityStatistics Canada
FundersNunavut Wildlife Management Board
KeywordsGeographyPer capitaWildlifeFood securityResource (disambiguation)Table (database)PopulationPopulation growthAgricultural economicsAgricultureEcologyDemographyBiologyArchaeologyEconomicsDatabase

Abstract

fetched live from OpenAlex

The security of the Inuit food system is the focus of extreme concern in Nunavut today. Despite this concern, little detailed analysis of the system’s traditional resource component has been done, primarily for lack of comprehensive recent information on harvesting. An exception is the harvest surveys carried out by the Nunavut Wildlife Management Board (NWMB) from 1996 to 2001. This comprehensive survey provides potentially important, albeit temporally limited (five year), information on recent Inuit wildlife use. To overcome this temporal limitation, we compared the NWMB data to information from the Baffin Regional Inuit Association (BRIA) 1980 to 1984 harvest survey for the 13 communities of the Qikiqtaaluk-Baffin Region. Together, these datasets provide two five-year “windows” on wild resource use in Nunavut’s most populous region. This comparison indicates declines in the total volume and per capita availability of wild foods in most communities relative to the early 1980s. We conclude that a partial cause for this change was hunters’ reduced access to monetary resources after the collapse of the European sealskin market (ca. 1983 – 84). When coupled with rising harvesting costs, this change significantly reduced the number of intensively engaged harvesters relative to the region’s growing population.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.057
GPT teacher head0.343
Teacher spread0.286 · 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

Citations13
Published2016
Admission routes4
Has abstractyes

Explore more

Same venueARCTICSame topicIndigenous Studies and EcologyFrench-language works237,207