Collaborative Interface Design and Language Archiving: The Case of Tsuut’ina
Bibliographic record
Abstract
This endeavor would not have been possible without Prof.Christopher Cox, who established the connection between me and members of Tsuut'ina Nation, participated in project meetings, and offered invaluable advice and feedback on drafting the present thesis.I would also like to express my deepest gratitude to the members of Tsuut'ina Nation who initiated this project and participated in the meetings for the development of the web-based interface: Janelle Crane-Starlight, Hanna Big Crow and Beric Manywounds.Lastly, I would be remiss in not mentioning my family and friends, who were there supporting me along the journey
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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 | 0.024 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".