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Record W7132975936

The Role of Canadian Bison Producers in Conserving the Plains (Bison bison bison) and Wood (Bison bison athabascae) Bison

2022· dissertation· W7132975936 on OpenAlexaboutno aff
Melissa Haley Heppner

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsBison bisonWildlifeLivestockWildlife managementWildlife conservationPopulation
DOInot available

Abstract

fetched live from OpenAlex

This project examines the curious tension between conservation and commercial livestock production in a case study of Plains bison (Bison bison bison) and Wood bison (Bison bison athabascae) in Canada. Despite a population of nearly 200,000 individuals, bison in Canada are species of conservation concern as over 90% exist in commercial production rather than for ecological conservation. Where conservation goals for bison include preserving wildness, genetic diversity, and ecological function, ranchers typically prioritize profits through artificial selection and intensive management. However, the Canadian Bison Association (CBA) — an organization committed to protecting the industry — has taken strides to identify with conservation. Interviews with CBA representatives and bison ranchers were conducted to understand the creation of and participation in conservation initiatives, as well as perspectives on the future of bison in Canada. Overall, the results inform bison conservation and contribute to the literature on stakeholder values in cross-jurisdictional wildlife conservation.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.004
Scholarly communication0.0040.001
Open science0.0010.002
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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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