“Recovering our Stories”: A Small Act of Resistance
Bibliographic record
Abstract
This paper describes a community event organized in response to the appropriation and overreliance on the psychiatric patient “personal story” within mental health organizations. The sharing of experiences through stories by individuals who self-identify as having “lived experience” has been central to the history of organizing for change in and outside of the psychiatric system. However, in the last decade, personal stories have increasingly been used by the psychiatric system to bolster research, education, and fundraising interests. We explore how personal stories from consumer/survivors have been harnessed by mental health organizations to further their interests and in so doing have shifted these narrations from “agents of change” towards one of “disability tourism” or “patient porn.” We mark the ethical dilemmas of narrative cooptation and consumption, and query how stories of resistance can be reclaimed not as personal recovery narratives but rather as a tool for socio-political change.
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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 | 0.019 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.053 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".