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Record W4251848950 · doi:10.32920/14639283

Survivor research in Canada: ‘Talking’ recovery, resisting psychiatry, and reclaiming madness

2021· preprint· en· W4251848950 on OpenAlexaboutno aff
Danielle Landry

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Rhetorical questionDistressPsychologyPsychoanalysisSociologyPsychiatryPsychotherapistLiteratureArt

Abstract

fetched live from OpenAlex

Beginning with discussion of what constitutes survivor research in Canada, this paper presents the findings of a critical discourse analysis of published accounts of survivor-led research over the last twenty-five years. Though they are varied, these texts demonstrate a rhetorical shift from a focus on the individual mind/body out to the social world experienced by psychiatric consumer/survivors. Findings indicate that survivor-led research engages with recovery discourse in numerous, sometimes problematic ways, in order to push back against dominant biomedical and psychiatric discourses. Further, new language is being generated for understanding madness and distress, rooted in a survivor perspective

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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.009
Science and technology studies0.0510.047
Scholarly communication0.0200.006
Open science0.0030.009
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.473
GPT teacher head0.495
Teacher spread0.023 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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