Indgenous Women's Speakers Series
Bibliographic record
Abstract
The Indigenous Women's Speakers Series is co-hosted by the Centre for Feminist Research, the Centre for Indigenous Knowledges and Languages and the Faculty of Health.\n\nSupported by the Office of the Vice President, Research and Innovation.\n\nSince 2017, the series has highlighted scholars working at the intersection of feminist and Indigenous scholarship.\n\nAbout the Speakers:\n\nKim Anderson, Métis, is an Associate Professor in the Department of Family Relations and Applied Nutrition at the University of Guelph where she holds a Canada Research Chair in Indigenous Relationships. Her books include A Recognition of Being: Reconstructing Native Womanhood (CSPI, 2nd Edition, 2016) and Life Stages and Native Women: Memory, Teachings and Story Medicine (University of Manitoba Press, 2011).\n\nDr. Jennifer Adese (otipemisiwak/Métis) is the Canada Research Chair (CRC) in Métis Women, Politics, and Community, and an Associate Professor in the Department of Sociology at University of Toronto Mississauga (UTM). She is the author of Aboriginal™: The Cultural & Economic Politics of Recognition (University of Manitoba Press) and the co-editor of A People and a Nation: New Directions in Contemporary Métis Studies (UBC Press), and Indigenous Celebrity (University of Manitoba Press). Her work has also been published in journals such as TOPIA, American Indian Quarterly, SAIL: Studies in American Indian Literatures, MediaTropes, Decolonization: Indigeneity, Education & Society (DIES), Public, and appears in select edited anthologies on Indigenous land rights, colonization, art, activism, and resistance
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.162 | 0.031 |
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".