Electro-Immobilization of Fishes for Surgical Implantation of Acoustic Tags: Advancing the Ethical Application of New Technology through the Incorporation of Mi’kmaw Values
Bibliographic record
Abstract
This essay explores how novel technologies can uphold Indigenous worldviews and ethical responsibilities, drawing on knowledge and experiences from the Apoqnmatulti’k (Mi’kmaw for “we help each other”) partnership as a case study. The project focuses on enhancing the understanding of valued aquatic species in two study regions within Mi’kma’ki (Nova Scotia, Canada). Central to this work is the use of acoustic telemetry, a method that involves surgically implanting transmitters into fish to monitor their movements and habitat use. While this technique provides otherwise unobtainable information on aquatic animal movements and can reveal insights regarding species behaviour, habitat connectivity, and population dynamics, the surgical methods raise important ethical considerations about animal welfare and potential ecological impacts. These considerations become even more complex when natural science research intersects with Indigenous cultural practices, food sovereignty, and long-standing relationships with aquatic species.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".