Identification of the Relationship Between Life Satisfaction and Narcissism Levels of University Students
Bibliographic record
Abstract
The objective of this study is to identify the relationship between life satisfaction and narcissism levels of students of the Physical Education and Sports School of Mardin Artuklu University located in southeastern Turkey. In the study, Satisfaction with Life Scale and Narcissistic Personality Inventory were employed in order to collect data. Sample of the study is comprised of a total of 155 Physical Education and Sports School students who voluntarily agreed to participate in the study. 56 participants were female and 99 participants were male. In the data analysis of this research, SPSS 20.0 software was utilized. Independent Samples T-Test, One-way Analysis of Variance (ANOVA) and correlation analysis were used in data analysis. At the end of the statistical analysis, it was found that female students had quantitatively higher narcissistic personality and life satisfaction scores than male students. Thus, it was inferred that female students behaved more narcissistically and were more engaged with life. However, along with the comparison of students’ narcissism and life satisfaction scores particularly on the basis of departments of Physical Education and Sports School at which students were enrolled, it was ascertained that there was no statistically significant difference in either narcissism scores or life satisfaction scores.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".