Anthropological futures for the study of cultural resilience of ‘Western’ societies in the face of climate change
Bibliographic record
Abstract
Climate change, as a scientifically defined global phenomenon, threatens the cultural resiliency of societies the world over. Anthropology has accrued a rich body of ethnographic research that has illuminated the potential of cultural resiliency for indigenous and non-Western societies. This information is vital for understanding the political, social, and economic movement of these societies. However, the same research focus and academic rigor has not been applied to non-indigenous, Western societies. These societies have been examined for economic and ecological resilience, but there is a detrimental vacuum of ethnographic understanding. Research relevant to climate change is restricted to etic, survey analysis. This research is invaluable but cannot resolve deeper “why” questions regarding political, social, and economic movements in the West. Furthermore, the survey data from within Canada is severely limited, making any analysis of non-indigenous Canadian society vague and riddled with caveats. This paper discusses the academic neglect regarding the cultural resiliency of non-indigenous, Western societies. From existing literature, the author constructs a research framework for Alberta, Canada—the province placed at the crux of the national climate change debate. Anthropological institutions must ask themselves why this demographic is excluded from the same critical analysis applied to indigenous and non-Western societies and move to correct this discrepancy.
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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 | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.080 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".