Shifting Seasons and Threats to Harvest, Culture, and Self‐Identity: A Personal Narrative on the Consequences of Changing Climate
Bibliographic record
Abstract
Abstract Northern Indigenous communities are experiencing rapid climate change and disrupted seasonal transitions. The Teetł'it Gwich'in use a five‐season calendar to measure the year, indicating the timing of seasonal events and associated cultural practices. From trapping in the spring, to fishing in the summer and fall, and hunting in the fall and winter, the Gwich'in have moved upon the land with the changing seasons. However, disrupted seasonal synchrony can disconnect cultural practices from suitable conditions, creating risks to self and culture. With warming temperatures, communities have observed slower river freeze‐up in the fall and faster spring thaw, which has impacted the timing of when fishers can safely set their nets under river ice. Historically, freeze‐up occurred in October, providing several weeks when fishers could set nets under ice while łuk dagaii (broad whitefish, Coregonus nasus) traveled downriver. Today, freeze‐up often begins in November, and fishing during the łuk dagaii migration requires setting nets while the ice is thinner and the river is not completely frozen. This presents risks to individuals working to maintain a fundamental cultural practice. Here, Arlyn Charlie, a Teetł'it Gwich'in artist whose career focuses on culture and language, uses personal narrative to explore impacts of climate change on Gwich'in culture. Arlyn notes how these changes are making the traditional seasonal calendar unreliable, and explores how changing patterns among animals and the landscape no longer provide consistent, safe harvesting conditions. With a growing risk of working on thin ice, ongoing cultural practices are threatened.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.020 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".