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Record W2158819391 · doi:10.1177/0959353512467974

The DSM and its lure of legitimacy

2013· article· en· W2158819391 on OpenAlexaff
Michelle N. Lafrance, Suzanne McKenzie-Mohr

Bibliographic record

VenueFeminism & Psychology · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsSt. Thomas University
Fundersnot available
KeywordsLegitimacyDistressFraming (construction)PsychologyStigma (botany)Mental illnessCriticismMeaning (existential)Dominance (genetics)Mental healthSocial psychologySociologyPsychiatryPsychotherapistPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

The Diagnostic and Statistical Manual of Mental Disorders (DSM) offers a biomedical framing of people’s experiences of distress and impairment, and despite decades of criticism, it remains the dominant approach. This dominance is maintained not only by powerful corporate interests such as the pharmaceutical industry, but also through the everyday talk of people as they attempt to make meaning of themselves and their experiences. This paper explores how and why the DSM holds such cultural currency for individual speakers, and unpacks what is being accomplished in their taking up the language of psychiatric diagnosis. In particular, we argue that a biomedical construction of distress offers the lure, or promise, of validating persons’ pain and legitimizing their identities. However, we also argue that the very assumptions of biomedicine ensure that this promise can never entirely be fulfilled and, despite its lure, a biomedical construction of ‘mental illness’ all too frequently fails to protect individuals from delegitimation and stigma.

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)0.050
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.050
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.064
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0080.071
Scholarly communication0.0110.015
Open science0.0020.010
Research integrity0.0070.018
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.034
GPT teacher head0.305
Teacher spread0.271 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations100
Published2013
Admission routes1
Has abstractyes

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