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Record W2155948706 · doi:10.1177/0308275x13510187

Worldviews and human–animal relations: Critical perspectives on bison–human relations among the Euro-Canadians and Blackfoot

2014· article· en· W2155948706 on OpenAlexafffund
Gerald A. Oetelaar

Bibliographic record

VenueCritique of Anthropology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsHuman animalPastoralismEnvironmental ethicsPerceptionSociologyEcologyGeographyLivestockEthnologyPsychologyBiology

Abstract

fetched live from OpenAlex

Researchers generally study human–animal relations in terms of hunter–gatherers, pastoralists or urbanites but few have explored the relationship between humans and the same animal across cultures. In this paper, I examine the relationship between humans and bison in the world of Euro-Canadians and the cosmos of the Blackfoot. Although both groups perceived the bison as a valuable resource and implemented conservation strategies to ensure its survival, their respective attitudes toward this species reflected very different worldviews. To Euro-Canadians and western researchers, the bison are perceived as being a part of nature, and thus human–animal relations change in tandem with the changing perceptions of the natural environment. To the Blackfoot people, humans are part of nature as are bison, and therefore, human–animal relations involve direct interactions between sentient beings.

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)0.005
metaresearch head score (Gemma)0.004
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 score0.066
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0330.054
Scholarly communication0.0090.004
Open science0.0020.005
Research integrity0.0020.004
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 head0.024
GPT teacher head0.381
Teacher spread0.357 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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