Accessing and Mobilizing “New” Data to Evaluate Emerging Environmental Impacts on Semi-Aquatic Mammals
Bibliographic record
Abstract
This paper describes how knowledge mobilization evolved during a study that assessed a proposed increase in industrial water withdrawals from the Athabasca River in northern Alberta, Canada, and potential impacts on a suite of freshwater semi-aquatic mammals in the broader ecosystem. The oil sands region in northeastern Alberta faces various pressures that require rapid knowledge mobilization and decision making, while still acknowledging ecological sensitivities immediately downstream in the Peace-Athabasca Delta (PAD) in the Wood Buffalo National Park. Data were acquired using a multi-faceted approach, including literature reviews, acquisition and synthesis of raw data, and interviews with local knowledge holders. The final outcome of the study was then contextualized relative to elements of knowledge mobilization: (1) research, (2) dissemination, (3) uptake, (4) implementation, and (5) impact. Knowledge mobilization was easiest to quantify for the first two elements, yet was still present in varying forms in the latter stages. The cultural importance of beavers, muskrats, river otters, and mink for communities associated with the Athabasca River and the PAD allowed for increased engagement during all stages of the research process, which then facilitated the co-production of potential solutions among different organization and perspectives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".