Deconstructing the academic narrative: Applying a determinants of health framework to identify the drivers of research on wood bison (<i>Bison bison athabascae</i>)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.105 | 0.141 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".