Research as Reciprocity: Northern Cree Community-Based and Community-Engaged Research on Wild Food Contamination in Alberta’s Oil Sands Region
Bibliographic record
Abstract
In this paper I suggest that it is possible to participate in research as an act of reciprocity; when a community asks a researcher for help on a specific topic, the application of that researcher’s skills can be one of the ways they show appreciation for being welcomed into a place. I also argue that a researcher needs to be sensitive to, and participate in, systems of respect and reciprocity belonging to the people, ancestors, and sentient landscape of the place they are doing research. I critique the extraction of traditional knowledge in the traditional land use consultation industry in Alberta, Canada that is used in place of the Federal Government’s duty to consult First Nations regarding their Treaty rights. As an alternative to traditional land use assessments I provide a description of the methods used in projects that test Fort McKay First Nation and Bigstone Cree First Nation’s wild foods for contaminants resulting from oil sands activities in northern Alberta’s Treaty No. 8 region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.028 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 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".