“It’s like a connection between all of us”: Inuit social connections and caribou declines in Labrador, Canada
Bibliographic record
Abstract
Many caribou populations are declining across the Circumpolar North, presenting challenges for many Indigenous Peoples who have deep and enduring relationships with this animal. In Labrador, Canada, caribou herds have recently experienced population declines, including the George River herd, which has dropped by 99% from its peak, leading to the enactment of a total hunting ban in 2013 issued by the Government of Newfoundland and Labrador. The decline and subsequent hunting ban have affected various aspects of Inuit well-being. Using Inuit-led multi-media methods, this project heard voices of Inuit across the Nunatsiavut and NunatuKavut regions in Labrador, Canada, which (1) described the importance of caribou for Inuit social connections, (2) explored the ways in which the changes in caribou populations and management strategies are influencing these social connections, and (3) discussed the meaning and value of these social connections for Inuit well-being and the sustainability of Inuit-caribou relationships into the future. Data from video interviews (Nunatsiavut region: n = 54; NunatuKavut region: n = 30) were collected and analyzed using video and photography-based methods. Results characterized how caribou are important social connectors: human-caribou relationships are core to Inuit socialization, inter-connection, and shared experience and memory regarding families, communities, and food and knowledge sharing across Labrador’s landscape. Thus, declines in caribou populations and associated social interaction have had serious implications for Inuit identity, livelihoods, emotional well-being, cultural continuity, and knowledge transfer. In order to support the broader social-ecological system and the well-being of those who are connected to caribou, increased understanding and integration of these social connections into caribou-related decision making and research is recommended.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".