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Record W4407591427 · doi:10.1002/2688-8319.70013

Deconstructing the academic narrative: Applying a determinants of health framework to identify the drivers of research on wood bison (<i>Bison bison athabascae</i>)

2025· article· en· W4407591427 on OpenAlexafffundabout
Alana Wilcox, Sarah Sine, André Morrill, Craig Stephen, Jennifer F. Provencher

Bibliographic record

VenueEcological Solutions and Evidence · 2025
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsEnvironment and Climate Change Canada
FundersEnvironment and Climate Change Canada
KeywordsNarrativeBison bisonGeographyEcologySociologyBiologyArtLiterature

Abstract

fetched live from OpenAlex

Abstract Conservation approaches that address complex and dynamic environmental challenges necessitate the dismantling of rigid academic boundaries and building effective interdisciplinary collaborations. The dominance of select disciplinary fields and/or interactions among diverse groups of researchers establishes the research narrative, ultimately guiding academic discussions and lending to conservation initiatives. We applied a determinants of health (DOH) framework to examine how research narratives have approached the health of wood bison ( Bison bison athabascae ), a species with at‐risk herds facing imminent threats to recovery, and how the potential for clustered narratives creates challenges for a comprehensive view of bison health. We conducted a literature review, coding for whether articles qualitatively or quantitatively analysed wood bison health, or provided contextual information, classifying articles into six distinct DOH. We found that articles principally analysed intrinsic and extrinsic biological factors related to wood bison health, but results were often contextualized in relation to the human expectations related to management, recovery and conservation of wood bison herds. We then examined author and institutional collaborations and timelines for publications of articles on wood bison health. We found that authors published research in multiple years, but authors with a high degree of collaborations were most often affiliated with academic, Canadian federal government or Canadian territorial government institutions. We show that wood bison health considers physical, social and human expectations related at individual wood bison and population levels. Practical implications . Our results also suggest that there are few mechanisms to integrate information across disciplines, which could cause problems for a comprehensive assessment of wood bison health. Nonetheless, interdisciplinary frameworks, such as One Health, that examine the intersection of animal–environment–human health present potential ways forward for the conservation of wood bison.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.333
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.207
GPT teacher head0.514
Teacher spread0.308 · 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.

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

Citations1
Published2025
Admission routes3
Has abstractyes

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