Relationships between Rangifer and Indigenous Well-being in the North American Arctic and Subarctic: A Review Based on the Academic Published Literature
Bibliographic record
Abstract
Many Rangifer tarandus (caribou or reindeer) populations across North America have been declining, posing a variety of challenges for Indigenous communities that depend on the species for physical and cultural sustenance. This article used a scoping review methodology to systematically examine and characterize the nature, extent, and range of articles published in academic journals on the connection between Rangifer and Indigenous well-being in the Arctic and Subarctic regions of North America. Two reviewers independently used eligibility criteria to identify and screen abstracts and titles and then screen full texts of each potentially relevant article. To be included in this review, articles had to discuss linkages between Rangifer and Indigenous well-being in the North American Arctic and Subarctic and be published prior to 2018. A total of 4279 articles were identified and screened for relevance; 58 articles met the inclusion criteria and were analyzed using descriptive quantitative and thematic qualitative methods. Results characterized the depth and diversity of what we know about Rangifer for Indigenous culture, food security, livelihoods, psychological well-being, and social connections across North America in the academic literature. Several gaps were identified. Little is known about the psychological ties between Rangifer and Indigenous Peoples and the influence of Rangifer-related change on Indigenous well-being and adaptive capacity. We urgently need to know more about the emotional connections that arise from Indigenous-Rangifer linkages, the effectiveness of adaptive strategies, and the intergenerational implications of Rangifer-related change. Further, enhanced inclusion of Indigenous Peoples in the production of knowledge on this topic is fundamental to the future of understanding Indigenous-Rangifer relationships.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".