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Record W2014090198 · doi:10.1177/0020764010387062

Examining differences in the stigma of depression and schizophrenia

2010· article· en· W2014090198 on OpenAlexaff
Ross Norman, Deborah Windell, Rahul Manchanda

Bibliographic record

VenueInternational Journal of Social Psychiatry · 2010
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsPsychologySchizophrenia (object-oriented programming)ClubDepression (economics)Clinical psychologySocial distanceStigma (botany)Social stigmaPsychiatryMedicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Although there is evidence of greater stigmatization of schizophrenia in comparison to depression, there has been little investigation of the reasons for this difference. AIMS: To examine the role of beliefs about depression and schizophrenia in mediating the difference in preferred social distance towards individuals with these two disorders. METHODS: In Study I, 200 undergraduates completed questionnaires concerning beliefs about depression or schizophrenia and willingness to interact with an individual who has one of the two disorders. In Study II, 103 members of a community service club completed similar measures. RESULTS: For both samples, beliefs about likely appropriateness of social behaviour showed evidence of mediating differences in preferred level of social distance. In addition, differences in perceived danger may have been a mediator for the undergraduate sample and perceived prognosis for the service club respondents. CONCLUSIONS: Beliefs about social appropriateness, danger and prognosis, which have implications for likely costs and benefits of interaction, are more likely to mediate differences in social distance towards the disorders than beliefs concerning causation or continuity with normal experience.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.375
Teacher spread0.338 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations67
Published2010
Admission routes1
Has abstractyes

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