Once Upon the Permafrost : Knowing Culture and Climate Change in Siberia
Bibliographic record
Abstract
Once Upon the Permafrost is a longitudinal climate ethnography about “knowing” a specific culture and the ecosystem that culture physically and spiritually depends on in the twenty-first-century context of climate change.\n\nThe author, anthropologist Susan Alexandra Crate, has spent three decades working with Sakha, the Turkic-speaking horse and cattle agropastoralists of northeastern Siberia, Russia. Crate reveals Sakha’s essential relationship with alaas, the foundational permafrost ecosystem of both their subsistence and cultural identity. Sakha know alaas via an Indigenous knowledge system imbued with spiritual qualities. This counters the scientific definition of alaas as geophysical phenomena of limited range. Climate change now threatens alaas due to thawing permafrost, which, entangled with the rural changes of economic globalization, youth out-migration, and language loss, make prescient the issues of ethnic sovereignty and cultural survival.\n\nThrough careful integration of contemporary narratives, on-site observations, and document analysis, Crate argues that local understandings of change and the vernacular knowledge systems they are founded on provide critical information for interdisciplinary collaboration and effective policy prescriptions. Furthermore, she makes her message relevant to a wider audience by clarifying linkages to the global permafrost system found in her comparative research in Mongolia, Arctic Canada, Kiribati, Peru, and Chesapeake Bay, Virginia. This reveals how permafrost provides one of the main structural foundations for Arctic ecosystems, which, in turn, work with the planet’s other ecosystems to maintain planetary balance.\n\nMetaphorically speaking, we all live on permafrost.\n\n
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".