Self-Advocacy from the Ashes of the Institution
Bibliographic record
Abstract
This paper explores the oral histories of two survivors of Canada’s institutions for persons labelled with intellectual disability. Both of these men survived the abuses of the institutions and went on to become committed to rights advocacy for others labelled with an intellectual disability. They were determined to tell their stories and act as change agents so that no one else experiences the abuse they did. In this paper, Peter and Martin tell parts of their stories, including their journey toward self-advocacy. This paper provides a space for these truths to be revealed in the time of class action law suits that are underway for these survivors. No opportunity was provided for the class action members to tell their stories in court, so this paper contains pieces of the narrative that survivors want people to know. Their stories are told in both narrative and art form. These artifacts highlight common themes of institutional abuse and isolation, but also of remarkable resiliency and strength. Their stories serve as an important record of the history of institutionalization in Canada and help to shape a better understanding of the roots of self- advocacy, including the importance of “nothing about us without us” (Charlton, 1998).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.037 | 0.025 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".