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Record W2996423745 · doi:10.1093/deafed/enz034

Emotional Functioning, Positive Relationships, and Language Use in Deaf Adults

2019· article· en· W2996423745 on OpenAlexaff
Cecilia Peñacoba, Daniel Garvi, Lourdes Gómez, Ana Álvarez

Bibliographic record

VenueThe Journal of Deaf Studies and Deaf Education · 2019
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsPsychologySign languageAlexithymiaDevelopmental psychologyInterpersonal communicationAssociation (psychology)Hearing lossInterpersonal relationshipClinical psychologyAudiologyLinguisticsSocial psychology

Abstract

fetched live from OpenAlex

This study aimed to explore emotional regulation, alexithymia, and interpersonal relations in a Spanish sample of 146 adult deaf participants and 146 typical hearing participants. For the deaf sample, the associations between type of language used and the above variables were also analyzed. Results showed that deaf participants scored higher on alexithymia and lower for positive relationships. However, no differences were found between deaf and typical hearing participants on emotional regulation. Regarding language use (Spanish Oral Language, SOL; Spanish Sign Language; or both), deaf participants used both languages in most contexts. Deaf participants who reported using SOL as their main mode of expression showed greater positive relationships than deaf participants who use both languages. Deaf participants who reported using both languages scored higher in emotional attention and emotional repair. These results evidence an association between the language use of deaf participants and alexithymia.

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)0.000
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 score0.046
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.041
GPT teacher head0.343
Teacher spread0.303 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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