Bibliographic record
Abstract
In its final report, the Truth and Reconciliation Commission of Canada called “… upon the federal government, in collaboration with Survivors and their organizations, and other parties to the Settlement Agreement, to commission and install a publicly accessible, highly visible, Residential Schools National Monument in the city of Ottawa to honour Survivors and all the children who were lost to their families and communities.” As we reckon with this “call to action” number 81, and bear witness to recent and ongoing public repudiation of contentious monuments, it becomes apparent that the logic of such a monument must be questioned. On the surface, it would appear that a counter or therapeutic monument (for which we have models) might best suit call 81’s objectives. I argue that the 144 Indigenous-led commemoration projects funded through the Indian Residential Schools Settlement, which reflect contemporary Indigenous commemorative approaches, forms, and practices for remembering and healing from traumatic pasts and their ongoing legacies, are those most relevant to the Residential Schools National Monument project. They can inform its process, design, siting, and programming, which may enable it to resist, counter, redefine, and perhaps even decolonize the “national monument.” In this article, I both critique call 81 and seek to contribute to this possibility.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.024 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 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".