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Record W2025065153 · doi:10.1080/01426397.2012.722612

Cree Hunters’ Observations on Resources in the Landscape in the Context of Socio-Environmental Change in the Eastern James Bay

2012· article· en· W2025065153 on OpenAlexafffundabout
Marie-Jeanne S. Royer, Thora Martina Herrmann

Bibliographic record

VenueLandscape Research · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversité de Montréal
FundersCanada Research Chairs
KeywordsSubsistence agricultureWildlifeGeographyBayContext (archaeology)WoodlandEnvironmental changeEcologyEnvironmental resource managementEnvironmental protectionClimate changeArchaeologyAgricultureEnvironmental science

Abstract

fetched live from OpenAlex

This article examines the understanding of Cree hunters in relation to shifts in landscape resources and in particular the availability of two key subsistence wildlife species (i.e. Canada geese and woodland caribou) as a result of climatic and socio-environmental changes and their subsequent impacts on Cree subsistence activities and Cree culture. These results are based on questionnaires and interviews conducted among Cree hunters of the Eastern James Bay. Findings indicate that a number of Cree are concerned with changes in the physical landscape, in sociocultural and intergenerational dynamics as well as shifts in wildlife distribution, which are impacting their ability to use the land and to maintain traditional subsistence activities. This research provides a deeper understanding of current and future trends in the Cree's relationship with landscape resources in the context of continuing change, necessary to future development of appropriate adaptation and landscape planning strategies to cope with occurring changes.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.946
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.242
GPT teacher head0.438
Teacher spread0.196 · 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

Citations11
Published2012
Admission routes3
Has abstractyes

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