Land and Language: The Struggle for National, Territorial, and Linguistic Integrity of the Oneida People
Bibliographic record
Abstract
The ability to maintain a living community is a functional requirement for the natural transmission of culture and language. The Oneida Indians, aboriginal people of what is now the State of New York, have struggled for more than two centuries to sustain their community and culture. The Oneidas have experienced and aggressive programme of expropriation, the division of the community, and the exile of the majority of their people to Canada and the State of Wisconsin. Only within the past few decades have the Oneidas begun to achieve some success in rebuilding their economic base and in reclaiming some of their native lands, but in the meantime their language has been almost entirely lost. They have attempted to use recent legal victories to rebuild their land base, their community, and their basis for cultural and linguistic transmission, but continue to confront a hostile and intimidating social and legal orientation on the part of the larger community, as well as divisive conflict among themselves. An examination of the case of the Oneidas illuminates the continuing impact of the European expansion into the Americans and of policies and practices that have been inimical to the retention of native cultures and languages.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".