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Record W231024138

アレキシサイミアと孤独感,ソーシャル・サポートとの関連

2007· article· ja· W231024138 on OpenAlexaboutno aff
美里 宮田, 健二 佐藤

Bibliographic record

Venuenot available
Typearticle
Languageja
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessAlexithymiaToronto Alexithymia ScalePsychologyFeelingExpectancy theorySocial supportUCLA Loneliness ScaleScale (ratio)Clinical psychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the relationship between alexithymia,loneliness, and social support. The participants were 313 undergraduate students (159 males and 154 females). Measures were Japanese version of the twenty-item Toronto Alexithymia Scale (TAS-20), Japanese version of the revised UCLA loneliness scale, and the Scale of Expectancy for Social Support. The participants were divided into three groups (higher, middle,and lower scores) on the basis of their scores on the TAS-20. Results showed that the higher the level of the alexithymia was,the higher the loneliness was. Moreover,it was revealed that the higher the level of the alexithymia was,the lower the expectancy for social support was. This study suggested that alexithymic individuals feel more loneliness,and have lower expectancy for social support than non-alexithymic individuals. It was discussed that the difficulties of identifying feelings and describing feeling,which are two aspects of alexithymia,may cause higher loneliness and lower expectancy for social support.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.017
GPT teacher head0.299
Teacher spread0.282 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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