Labour dynamics, harvest cost and sharing behaviour in an Inuit mixed economy: How to adapt to a changing socio-ecological system?
Bibliographic record
Abstract
The transition to a wage-based economy has altered the traditional sharing of country food practiced in many Northern communities, yet the degree of impact is relatively unknown. The trading of traditionally shared foods may not benefit everyone equally in the community, and decreased sharing may negatively impact vulnerable households that historically received food through the sharing networks. Sharing behaviour may also be linked to spatiotemporal variation in the availability of harvested species, the cost of hunting and fishing and labour market status of harvesters. We present the results of a multi-year harvest study paired with a socio-economic survey conducted in Gjoa Haven, Nunavut. We strive to identify the direct and indirect costs associated with harvesting country food, socioeconomic barriers to harvesting, seasonal trends in harvesting, and how these factors interact to influence sharing behaviour. We investigate the costs and benefits of hunting and fishing efforts, and the relationship between employment and harvest and sharing practices. We examine the distribution of country food, and how sharing varies by season, type of hunter, group size and mode of transport. We discuss insights for current hunter support and food security programmes, and a potential guaranteed basic income for households in a mixed economy.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".