Bibliographic record
Abstract
Indigenous children were taken from their families and placed in residential schools since the 1870s and until 1996 in Canada with the aim to “kill the Indian in the child.” A Truth and Reconciliation Commission (TRC) was formed in 2008 to provide victims of these schools the opportunity to recount their experiences in a safe and culturally appropriate manner. After five years of gathering these experiences, the TRC report summarizes what was heard, and identifies 94 calls to action. We will show how numbers are used and not used in two TRC documents. We identify the value of such analysis for school and university mathematics teachers as an example of a culturally situated use of number for rhetorical purposes, which relates to the ideas of culturally responsive teaching and critical mathematics education. Not only does this kind of learning address calls for democratic and critical citizenship, it belongs in Canada’s new age of responsiveness to Indigenous experiences of colonialism.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.074 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".