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Record W2969751061 · doi:10.1177/0963662519868969

The critical reception of the <i>DSM-5</i>: Towards a typology of audiences

2019· article· en· W2969751061 on OpenAlexaff
Mélissa Roy, Marie-Pier Rivest, Dahlia Namian, Nicolas Moreau

Bibliographic record

VenuePublic Understanding of Science · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsUniversité de MonctonUniversity of Ottawa
Fundersnot available
KeywordsCriticismTypologyNaturalismAssociation (psychology)Meaning (existential)PsychologyCommon groundNarrativeHumanismSociologyNarratologyArgumentativeEpistemologySocial psychologyPsychotherapistLinguisticsLaw

Abstract

fetched live from OpenAlex

Since its initial publication, the Diagnostic and Statistical Manual of Mental Disorders has been the object of criticism which has led to regular revisions by the American Psychiatric Association. This article analyses the debates that surrounded the publication of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Building on the concepts of public arenas and reception theory, it explores the meaning encoded in the manual by audiences. Our results, which draw from a thematic analysis of traditional and digital media sources, identify eight audiences that react to the American Psychiatric Association’s narrative of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.): conformist, reformist, humanist, culturalist, naturalist, conflictual, constructivist and utilitarian. While some of their claims present argumentative polarities, others overlap, thus challenging the idea, often presented in academic publications, of a fixed debate. In order to further discuss on the Diagnostic and Statistical Manual of Mental Disorders, we draw attention to claims that ‘travel’ across different communities of audiences.

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)0.035
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0170.052
Scholarly communication0.0230.022
Open science0.0020.019
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.125
GPT teacher head0.314
Teacher spread0.189 · 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.

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

Citations22
Published2019
Admission routes1
Has abstractyes

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