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Record W4400456398 · doi:10.1080/10871209.2024.2374348

Alberta hunter knowledge and beliefs about the threat of zoonotic diseases in Canadian wood bison

2024· article· en· W4400456398 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHuman Dimensions of Wildlife · 2024
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of Calgary
FundersParks Canada
KeywordsGeographyWildlifeBison bisonEcologyBiology

Abstract

fetched live from OpenAlex

We evaluated whether knowledge of zoonotic diseases is related to beliefs about the threat of those diseases in wood bison. An online questionnaire of Alberta hunters (n = 239) was primarily conducted through the provincial government’s hunter licensing system. Respondent knowledge of bovine tuberculosis and brucellosis in Canada was limited and non-linearly related to threat beliefs. Higher knowledge was associated with believing the diseases are or are not a threat to human health rather than being unsure. Respondents were clustered based on their agreement that the diseases are threats to personal health. The Strongly Disagree cluster had significantly higher knowledge than the Neutral cluster. The Higher Agreement cluster had higher knowledge than the Neutral and lower knowledge than the Strongly Disagree clusters, but these differences were not significant. Results highlight how conflict could arise if increasing disease knowledge is assumed to lead to specific changes in disease threat-related beliefs.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.310
Teacher spread0.289 · 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