“When our words are put to paper.” Heritage documentation and reversing knowledge shift in the Bering Strait region
Bibliographic record
Abstract
The paper examines the relationship between indigenous knowledge and heritage documentation efforts generated by scientists and other forms of local activities that work in strengthening indigenous cultural identity and tradition. As the studies in indigenous heritage and environmental knowledge have become one of the fastest-growing fields in northern cultural research, there is tough competition for limited resources and, even more, for the time, goodwill, and attention of northern constituencies. Scholarly projects in heritage and knowledge documentation represent just one stream within today's public efforts, though an important and visible one. Those projects do have an impact in local communities; but such impact is often subtle, circumstantial, and may not be sustainable when left standing on its own. Local knowledge, very much like active language, relies primarily on oral transmission, family ties, community events, and subsistence activities. As long as those prime channels of cultural continuity are working, “our words put to paper”—knowledge and heritage sourcebooks, school materials, and catalogs—should be regarded as long-term cultural assets that may play a crucial role in the transformed northern societies of today and of tomorrow.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".