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Record W7111401219 · doi:10.5281/zenodo.17629283

ÜNİVERSİTE ÖĞRENCİLERİN NARSİSTİK KİŞİLİK VE ALEKSİTİMİ KİŞİLİK ÖZELLİKLERİ ARASINDAKİ İLİŞKİNİN ARAŞTIRILMASI

2025· article· tr· W7111401219 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languagetr
FieldHealth Professions
TopicProblem Solving Skills Development
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)Significant differenceData collectionResearch methodologySample (material)

Abstract

fetched live from OpenAlex

Yapılan bu çalışmanın amacı, Çanakkale 18 Mart Üniversitesinde spor bilimleri alanında okuyan öğrencilerin narsistik kişilik ve aleksitimi kişilik özellikleri arasındaki ilişkiyi ortaya koymaktır. Çalışmanın evrenini, spor bilimleri fakültesinde okuyan bütün öğrenciler oluştururken; örneklemini ise, çalışmaya gönüllü olarak katılmayı kabul eden 210 öğrenci oluşturmaktadır. Çalışmada veri toplama aracı olarak, Toronto Aleksitimi Ölçeği Kısa Versiyonu (TAÖ- 20) ve Narsistik Kişilik Envanteri kullanılmıştır. Elde edilen verilerin analizinde SPSS 20 programı kullanılmıştır. Elde edilen verilerin analizinde ilk olarak homojenlik ve normallik dağılımına bakılmıştır. Bunun için Kolmogorov-Smirnov (K-S) ve Shapiro Wilks testleri kullanılmıştır. Bu incelemeden sonra verilerin analizinde non parametrik test yöntemi kullanılmaya karar verilmiştir. Verilerin analizinde; tanımlayıcı istatistik, ve spearman korelasyon analizi uygulanmıştır. Elde edilen verilerin analizi sonunda, Narsisizm ile Dışa dönük düşünce, Duyguları söze dökmede güçlük, Duyguları tanımada güçlük, Toplam Aleksitimi arasında istatistiksel olarak anlamlı bir ilişki belirlenmemiştir.

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.

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0140.001
Scholarly communication0.0020.001
Open science0.0060.009
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0480.081

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 head0.049
GPT teacher head0.324
Teacher spread0.275 · 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