Bibliographic record
Abstract
In this set of collected, connected conversations (the penultimate episode in our Summer '22 series): Neech the Vote! Was it really a year ago that Canada held its last federal election? A contest we didn't much concern ourselves with, to be frank; after all, we'd gone hard on the election two years prior. But, looking back, maybe that 2019 campaign taught us all we needed to know about how Indigenous interests fare in such settler exercises. Featured voices this podcast include (in order of appearance): • Hayden King, Executive Director of the Yellowhead Institute based at Toronto Metropolitan University • Vanessa Watts, Yellowhead fellow and Assistant Professor of Indigenous Studies and Sociology at McMaster University • Kim TallBear, Professor in the Faculty of Native Studies at the University of Alberta and Canada Research Chair in Indigenous Peoples, Technoscience and Society • Brock Pitawanakwat, Associate Professor of Indigenous Studies at York University • Ken Williams, Assistant Professor with the University of Alberta's Department of Drama • Therese Mailhot, author and Assistant Professor of English at Purdue University • Candis Callison, Associate Professor in the Institute for Critical Indigenous Studies and the Graduate School of Journalism at UBC // CREDITS: Creative Commons music in this episode includes \\"really beautiful my mambo\\" and \\"Regate\\" by Jean Toba, \\"Treasure finding,\\" \\"Love Planet,\\" and \\"Night in a Seashell\\" by Komiku, \\"Rien n'a vraiment change\\" by Demoiselle Doner, and \\"Respect\\" by Alpha Hydrae. Our opening theme is \\"Bad Nostalgia (Instrumental)\\" by Anthem of Rain; our closing theme is \\"Garden Tiger\\" by Pictures of the Floating World. This episode was hosted/produced/edited by Rick Harp; production assistance by Courteney Morin.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.947 | 0.014 |
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; both teacher heads agree on what is shown here.
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".