Bibliographic record
Abstract
The global decline of anguillid eels is well-documented across all continents where nineteen related species migrate. In North America, the population decline (and in some cases, extirpation) is related to numerous factors including industrial development. Eels experience violent mortality and migration barriers which have been linked to extractive infrastructure affiliated with settler colonial land occupation. The intricate migration pattern of Anguilla rostrata (American eels) is one of those species, an ecologically significant fish that has ancestral and persistent relevance to First Nations and tribal nations in Canada and the US, respectively. This paper draws from Anishinabe ontological grounding including intergenerational dodem gikendaasowin (clan or kinship knowledge) to suggest that humans are living in a world that includes an aquatic governance mediated by eels. A primary contribution is the suggestion that attention to such framing has applied relevance to intergenerational land-based healing, for extension of ongoing pursuits including Indigenous environmental justice, water governance strategies, and renewed interspecies relations. The application of these nascent concepts affects possibilities for current and future generations to exert reflective capacity and advocate for greater decision-making in matters of water governance. This paper suggests these opportunities be afforded to inheritors of ancestral Anishinabeg legacy dispersed throughout areas in Anishinabe-aki, where eels have resided and migrated and may do so again; to survive, eels benefit from informed policy and governance practices that facilitate physical assistance. New regimes may be built from human reflexivity and the desire to give back to life, an inherent principle of Anishinabe water governance and the application of Nibi Inaakonigewin (water laws).
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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 | 0.000 | 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 | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".