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Emotional Intelligence as a Predictive Variable of Alexithymia Among Students with Hearing Impairments

2025· article· en· W4414293796 on OpenAlexaboutno aff
Amany Ghareeb Abd El azez

Bibliographic record

VenueCollege of Special Education Journal · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScaleEmotional intelligenceCorrelationScale (ratio)

Abstract

fetched live from OpenAlex

The current research aims to study the relationship between alexithymia and emotional intelligence, and the possibility of predicting alexithymia among students with hearing impairments, based on the level of emotional intelligence, in light of the importance of emotional intelligence as an influential factor in the psychological and social adaptation of this group. The researcher used the descriptive correlational approach, and the research community consisted of secondary school students at the School for the Deaf and Hard of Hearing in Suez Governorate, where the number of members of the basic sample amounted to (50) male and female students. The Toronto Alexithymia Scale (TAS-20) and the modified Scott Emotional Intelligence Scale were applied, after verifying their psychometric properties of the scales, on a standardized sample of (102) male and female students from secondary school students at schools for the deaf and hard of hearing in Ismailia and Port Said Governorates. The research results showed the existence of a negative and statistically significant correlation between alexithymia and emotional intelligence among students with hearing disabilities at a significance level of (0.01). The results also indicated that the degree of alexithymia could be predicted through the level of emotional intelligence. The results did not show any statistically significant differences in alexithymia or emotional intelligence attributable to the variables of gender or degree of disability (moderate-severe).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.994

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)0.0070.000

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 head0.023
GPT teacher head0.307
Teacher spread0.284 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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