Co-developing Openness: Indigenous Knowledge and Data Governance and Open Science in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Open science (OS) is a movement towards making the scientific process, and its outputs, more, transparent, accessible, inclusive, and credible, and OS has become a Government of Canada policy including the Canadian Commission for UNESCO. But how does open science impact Indigenous knowledge and data governance? Indigenous knowledge (IK) and Indigenous data and information challenge typical data and information norms in how they are collected, used, disseminated, and governed. As the Government of Canada is working to advance reconciliation and renew the relationship with Indigenous Peoples, there is an increased focus on institutionally recognizing and promoting the Indigenous right to knowledge and data governance. Although open science will likely increase the accessibility of scientific outputs, including research and knowledge published according to open standards, it is reasonable to assume that some of this research will include local and traditional knowledge and/or Indigenous data and therefore an OS framework should be developed in a way that prioritizes Indigenous knowledge and data governance.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.010 | 0.042 |
| Open science | 0.017 | 0.012 |
| 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 it