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Record W2052604421 · doi:10.2174/157340006778018184

Social Cognition Deficit in Schizophrenia: Accounting for Pragmatic Deficits in Communication Abilities?

2006· article· en· W2052604421 on OpenAlexaff
Maud Champagne‐Lavau, Émmanuel Stip, Yves Joanette

Bibliographic record

VenueCurrent Psychiatry Reviews · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsUtterancePsychologyCognitionLiteral and figurative languageCognitive psychologyLiteral (mathematical logic)Context (archaeology)Social cognitionSchizophrenia (object-oriented programming)Theory of mindLinguisticsNeuroscience

Abstract

fetched live from OpenAlex

Schizophrenic individuals show impairments in language affecting what is referred to as the pragmatic component of language, typically the processing of non-literal language (e.g., irony, metaphor, indirect request). Such non-literal utterances require the ability to process the speakers utterance beyond its literal meaning in order to allow one to grasp the speakers intention by reference to the contextual information. This paper gives a selective literature review showing that different cognitive processes-specific to language or not-may underlie the processing of pragmatic aspects of language, and particularly of non-literal language in schizophrenia. Indeed, the fact that many other disorders (e.g., right hemisphere lesion, traumatic brain injury, autism) are characterized by pragmatic impairments may reflect a heterogeneous range of underlying functional deficits that have to be determined. Evidence is reviewed suggesting that cooccurrence of a deficit in non-literal language understanding and a deficit in theory of mind may be accounted for by an impairment in context processing associated with a lack of flexibility. Keywords: Social cognition, non-literal language, theory of mind, context, executive function, schizophrenia

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.057
GPT teacher head0.354
Teacher spread0.296 · 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 designTheoretical or conceptual
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

Citations25
Published2006
Admission routes1
Has abstractyes

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Same venueCurrent Psychiatry ReviewsSame topicNeurobiology of Language and BilingualismFrench-language works237,207