Growing together: enhancing stewardship of American eel/katew in Atlantic Canada/Mi'kma'ki using diverse ways of knowing
Bibliographic record
Abstract
Widespread decline in American eel/katew (Anguilla rostrata) abundance has occurred in recent decades due to habitat fragmentation, changing marine conditions, and over-harvesting. American eel is a culturally and economically significant species, whose health and future in the Bay of Fundy/Pekwitapa'qek is of concern for everyone living in Atlantic Canada/Mi'kma'ki. There are few studies describing how American eel use Minas Basin, a highly productive, macrotidal area of the inner Bay of Fundy. My research, guided by Two-Eyed Seeing and in collaboration with diverse knowledge holders, explores the distribution and coastal movements of American eel in Minas Basin using acoustic telemetry. Results reveal the diverse habitats, residencies, and movement patterns of American eel in Minas Basin, with evidence of selective tidal stream transport. Network analysis indicates importance of river mouths for movement and suggests breaks in connectivity at these areas may have disproportionate impacts on local eel. This information provides knowledge for predicting impacts on local components of the eel population and provides an example of partners from diverse knowledge systems working towards co-stewardship.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".