The gifts of multiple perspectives: a Two-Eyed Seeing approach to Gumegwsis (Cyclopterus lumpus) ecology in inner Mawipoqtapei (Chaleur Bay), Eastern Canada
Bibliographic record
Abstract
The weaving of diverse knowledge systems, including Indigenous, Local, and Western Knowledge, is an increasingly adopted approach in scientific research and is perceived as a promising path towards advancing knowledge and management of coastal areas and fisheries management in Canada. Despite documented successes, skepticism among scientists and decision-makers persists, leaving unaddressed gaps. Here, in response to concerns voiced by fishers from the Mi’gmaw community of Ugpi’ganjiq, the Gespe’gewa’gi Institute of Natural Understanding (GINU) co-created a project to improve understanding of the ecology and state of the threatened Gumegwsis (i.e. Cyclopterus lumpus , common lumpfish) in inner Mawipoqtapei (Chaleur Bay, Eastern Canada). Through a Two-Eyed Seeing approach, we combined semi-structured interviews with five Knowledge Holders with a literature review, mapping, and temperature monitoring. Utilizing this Mi’gmaw framework, we learned about Gumegwsis life history in inner Mawipoqtapei, its significance to local fishers, changes in abundance over time, threats to the species, and identified potential areas for spawning and nursery habitats. Prior to our project, the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) assessment asserted “There are no indications of any ceremonial uses of Lumpfish in Canada and there is no ATK (Aboriginal Traditional Knowledge) information available”. In contrast, our study reveals the distinctive relationship and comprehension of Gumegwsis held by Mi’gmaw fishers, underscoring the significance of embracing multiple ways of knowing towards understanding species ecology, and presenting a compelling case for co-creation of species recovery strategies and collaboration in fisheries research.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.031 | 0.022 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| 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".