Simulated data and code from: Socio-economic predictors of Inuit hunting choices and their implications for climate change adaptation
Bibliographic record
Abstract
These data are part of a data portal that accompanies the special issue ‘Climate change adaptation needs a science of culture,’ published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit 10.5061/dryad.bnzs7h4h4. Summary Repository of R and Stan code to simulate and analyse foraging trip data (patch choice and harvest success). Accompanying manuscript F. Hillemann, B. A. Beheim, E. Ready. 2023. Socio-economic predictors of Inuit hunting strategies and their implications for climate change adaptation. Phil. Trans. R. Soc. B 378: 20220395. https://doi.org/10.1098/rstb.2022.0395 Manuscript Abstract:In the Arctic, seasonal variation in the accessibility of the land, sea ice, and open waters influences which resources can be harvested safely and efficiently. Climate stressors are also increasingly affecting access to subsistence resources. Within Inuit communities, people differ in their involvement with subsistence activities, but little is known about how engagement in the cash economy (time and money available) and other socio-economic factors shape the food production choices of Inuit harvesters, and their ability to adapt to rapid ecological change. We analyse 281 foraging trips involving 23 Inuit harvesters from Kangiqsujuaq, Nunavik, using a Bayesian approach modelling both patch choice and within-patch success. Gender and income predict Inuit harvest strategies: while men, especially men from low-income households, often visit patches with a relatively low success probability, women and high-income hunters generally have a higher propensity to choose low-risk patches. Inland hunting, marine hunting, and fishing differ in the required equipment and effort, and hunters may have to shift their subsistence activities if certain patches become less profitable or less safe due to high costs of transportation or climate change (e.g., navigate larger areas inland instead of targeting seals on the sea ice). Our finding that household income predicts patch choice suggests that the capacity to maintain access to country foods depends on engagement with the cash economy.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".