Bibliographic record
Abstract
This study aims to examine the mediating role of the level of alexithymia in the relationship between smartphone addiction and identity functions. The study group included 460 participants who were students attending Anatolian High Schools in four districts of Istanbul, and they were identified by a simple random sampling method. In this study, the Smartphone Addiction Scale-Short Version, the Identity Function Scale, the Toronto Alexithymia Scale, and a personal information form were used. The structural equation model (SEM) and bootstrapping were utilized to test the mediation analysis of the research. In the results of the analysis, it was found that smartphone addiction in high school students negatively predicted identity function (β = −0.37; p < .01), but positively predicted the alexithymia level (β = 0.43; p < .01). In addition, it was found that the alexithymia level of high school students negatively predicted identity function (β = −0.43; p < .01). Finally, it was concluded that the alexithymia level in high school students mediates smartphone addiction to predict identity functions (β = −0.19; p < .01). The model fit values were also found to be within acceptable values (χ2/df = 2.12, p < .0.1, RMSA = 0.05, SRMR = 0.05, GFI = 0.91, CFI = 0.94, TLI = 0.93).
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".