The Paq'tnkek Mi'kmaq and Ka't (American Eel): A Case Study of Cultural relations, Meanings and Prospects
Bibliographic record
Abstract
The Mi’kmaq have a deep and rich relationship with Ka’t (American eelAnguilla rostrata). While the Mi’kmaq continue to harvest Ka’t for food, their relations with and use of eel also embody important cultural meanings and practices. Ka’t occupies a notable place within many ceremonial settings, is used for medicinal purposes and, as a consequence of the ways in which Ka’t is shared, is central to traditional relations of reciprocity. Over recent decades, however, the commercialisation of eel fishing in Atlantic Canada has led to a decline in their numbers and has contributed to a significant reduction in eel fishing and eel use among the Mi’kmaq. Loss of access to eel may well translate into a much broader process of cultural loss, as the ceremonial and sharing practices centred on the fishing and consumption of eel disappear. However, legal precedents affirming treaty entitlements are positioning the Mi’kmaq to assume a more proactive role in managing both commercial and food fisheries. This paper reviews recent trends and discusses these issues with reference to the results of research carried out with Paq’tnkek (Afton), a Mi’kmaq community in northeastern Nova Scotia. The Paq’tnkek Mi’kmaq relations with Ka’t are described and discussed with respect to their cultural meanings and prospects. Implications for the revitalisation and empowerment of indigenous cultures are drawn from the lessons evident in this case study.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".