Giving back to the language community: lessons from the Kiowa and Ojibwe peoples
Bibliographic record
Abstract
In this paper, I discuss two very different language communities: the Kiowa tribe in southwestern Oklahoma and the Saulteaux Ojibwe first nation in Manitoba. Kiowa is a critically endangered language with only 10 native speakers, all nearing the age of 90. Revitalization efforts have been intermittent over the last 40 years, and little has helped. Saulteaux Ojibwe, while also endangered, is much healthier with 10,000 native speakers, some of whom are teachers with linguistic training actively conducting their own research. Drawing from my experience, I show that these marked differences lead to distinct needs and thus different directions for researchers to give back to the communities. I detail two general approaches that any linguist should be able to adopt in similar communities. The Kiowa tribe has little access to audio recordings of their language because the recordings were not digitized and/or copies were never provided. They have not seen a number of the resulting papers and books from previous researchers, and the only comprehensive dictionary is from the 1920s. In the words of one of my consultants: “If there was a dictionary with the sounds, too, I could die. I’m one of the last ones who knows how you’re supposed to pronounce things, and it will be lost forever without something like that.” While it is true that not everyone is equipped to commit to a full dictionary project, by doing research as we would anyway we can still make a big impact. Namely, a linguist can amass the available data in preparing their own research (search for previous recordings, contact other scholars, scan articles and books) and also be sure to give copies of those materials directly to the community (e.g. a museum, library, or community center). There are already online dictionaries and educational applications for the many dialects of Ojibwe, making research and data more readily available to the community and interested researchers. Thus, the community requires a markedly different approach than that of the Kiowa tribe. Namely, the Saulteaux Ojibwe community’s language teachers and researchers, working on the front lines of language revitalization, are seeking validation and support. In the spirit of more collaborative fieldwork (e.g., Mannix et al. 2015, Brooke Lillehaugen p.c.), we should look to work with the native community in the production and dissemination of the research (e.g. co-authoring papers, presentations, and grants), bringing our skills (and data) to the table of ongoing projects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".