Bibliographic record
Abstract
There has been more talk but not enough action on reconciliation since the Truth and Reconciliation Commission (TRC) released its final report in 2015 containing ninety-four calls to action (Truth and Reconciliation Canada 2015). Indigenous people have not experienced the reconciliation intended in the actions that Canada has agreed to implement. Indigenous people and all Canadians need to hold Canada accountable to these actions for true reconciliation to manifest in Canadian society. The TRC calls to action and the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) hold particular meaning and hope for me, as a survivor of Indian Residential Schools (IRS), and many other survivors who have gone through the TRC process. Truth is the first step toward reconciliation; understanding is the second step, and remediation is the third. Water is sacred. Protecting the water and asserting our rights in the Peace and Friendship Treaties are my responsibilities as a Mi’kmaw woman and rights holder. They are also an integral aspect of my healing journey. When I acknowledge Canadians’ habitation on the unceded lands of the Mi’kmaq, I mean that acknowledgment from the core of my spirit, the spirit of my ancestors, and my future generations. I am living that acknowledgment.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.038 | 0.038 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".