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Record W4248908327 · doi:10.53350/pjmhs211593050

An Investigation of Relationship Between Alexithymia and Ego-Oriented Levels of Students at The Faculty of Sports Sciences

2021· article· en· W4248908327 on OpenAlexaboutno aff
Emré Belli, Davut Budak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicProblem Solving Skills Development
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaTurkishPsychologyId, ego and super-egoToronto Alexithymia ScalePearson product-moment correlation coefficientClinical psychologySocial psychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

Aim: The aim of this study is to investigate of students sport science faculty relationship between on their alexithymia status and ego-oriented goals levels to compare them according to different demographic variables. Methods: For data collection, “Alexithymia Scale” was used which was developed by Bagby et al. 5 and was adapted to turkish by Güleç et al. 6 For data collection, “Task and Ego Oriented Scale” was used which was developed by Duda. 7 and was adapted to turkish by Toros and Yetim 8 to 416 participants in total consisting of 138 female and 278 male students. For data analysis, through SPSS statistical packet program, frequency analysis, desciptive statistics, independent sample t-tests, one-way anova, tukey, pearson correlation analyze were performed. Results: A highly significant negative correlation was found between the participants' ego orientation averages and their alexithymia averages. (r= -.826, p<0.01). Conclusion: According to this; As the participants' alexithymia levels increased, their ego orientation decreased; in other words, it was concluded that as ego orientations increased, alexithymia levels decreased. Keywords: Alexithymia, Ego-oriented, Physical Educaiton, Sport.

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 score0.002
Threshold uncertainty score0.006

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.162
GPT teacher head0.453
Teacher spread0.292 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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