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Perception of emotions in anxious and learning disabled children

2000· article· en· W2006672897 on OpenAlexaff
Katharina Manassis, Arlene Young

Bibliographic record

VenueDepression and Anxiety · 2000
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoCentre for Addiction and Mental HealthSickKids Foundation
Fundersnot available
KeywordsPsychologySadnessPerceptionNormativeAnxietyAudiologyDevelopmental psychologyAuditory perceptionClinical psychologyAngerPsychiatryMedicine

Abstract

fetched live from OpenAlex

This study examined differences in the ability to perceive others' emotions in anxious and learning disabled children, as these differences may contribute to these children's unique socio-emotional difficulties and therapeutic needs. Forty-six children ages 8 to 12 with either anxiety disorders (ANX), language-based learning disabilities (LD), both conditions, or neither condition (clinical controls) were compared on the DANVA, a standardized measure of auditory and visual perception of emotion. Group results were then compared to normative data. Using multivariate analyses, significant group differences were found on the auditory portion of the DANVA but not on the visual portion. LD and comorbid children scored lower on several auditory stimuli, especially when presented at low emotional intensity, while ANX and comorbid children showed high accuracy for auditory sadness. Comorbid children also had lower auditory DANVA scores than the normative sample. No interactive effects between ANX and LD were found. ANX and LD each appear to have distinct effects on the auditory perception of others' emotions. Children with both conditions show both effects and differ from normal children in this domain. Replication using larger samples is required.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.255
Teacher spread0.250 · 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 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

Citations29
Published2000
Admission routes1
Has abstractyes

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