Setting a foundation for Indigenous knowledge systems‐guided boreal caribou (tǫdzı) conservation planning in the Western Boreal Region of Canada: A systematic map protocol
Bibliographic record
Abstract
Abstract In recent years, researchers have increasingly recognized the need to bridge Western and Indigenous knowledge systems to strengthen research in wildlife conservation. Historically, this arena has not made space for Indigenous knowledge holders to share components of their knowledge systems with agency and to support their own self‐determination as equal partners. Since time immemorial, Indigenous Peoples have been developing, maintaining and refining their own knowledge systems, based on intimate knowledge and relationships with the lands, airs, and waterways. There remains enormous potential for Western scientists to engage in equitable knowledge exchange and co‐production with Indigenous Peoples. This applies to species such as boreal caribou Rangifer tarandus caribou , known by the Dene name, tǫdzı; which hold ecological value and cultural importance for both Indigenous and non‐Indigenous people in the boreal region of Canada. To gain an overarching perspective of this species, we will create a systematic literature map that will examine peer‐reviewed and grey literature involving spatial mapping of all species of caribou Rangifer tarandus based on Indigenous knowledge. This map will (a) characterize available data and previously engaged knowledge holders and (b) identify positive experiences that exemplify best practices for knowledge co‐production. Searches will be conducted in English in selected databases. Search strings will be tested against a collection of benchmark papers of documents previously chosen to determine strings with maximum sensitivity and specificity. Results will be reviewed through the: (1) title and abstract; and (2) full text. All screening decisions will be recorded in a database, with 10% of full‐text screening decisions validated. Items retained for inclusion in the systematic map will be coded using a list of coding questions. Ten percent of coding outcomes will be validated by a second reviewer. The systematic map will employ a narrative synthesis approach that will compare retained studies against a list of best practices from the current proposal. It will examine case studies that performed well according to the list and contribute to a repository of previously documented Indigenous knowledge about caribou to support projects involving Indigenous and Western knowledge co‐production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".