Perspectives on Openness: Honouring Indigenous Ways of Knowing
Bibliographic record
Abstract
York University Libraries Open Access Week 2020 panel discussion entitled, "Perspectives on Openness: Honouring Indigenous Ways of Knowing", moderated by Stacy Allison-Cassin, in conversation with Alan Ojiig Corbiere, Deborah McGregor, and Sean Hillier, that took place online on October 20, 2020. The theme for Open Access Week 2020 is Open With Purpose: Taking Action to Build Structural Equity and Inclusion. The basis of the discussion for the panel is the question, "In an era of open scholarship and research, how do we as a research community navigate and balance openness while respecting Indigenous knowledge and cultural expression?". This panel discussion offers the opportunity to encourage broader participation in conversations and actions around emerging scholarly communication issues, by centering on Indigenous approaches to open scholarship and research.
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 | 0.026 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.054 |
| Scholarly communication | 0.023 | 0.025 |
| Open science | 0.001 | 0.023 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".