Proposal for an empirical model of mentalization for clinical and research purposes
Bibliographic record
Abstract
Mentalization is a psychological construct that has gained more and more attention over the last few years. Despite this growing interest, researchers have emphasized its multidimensional and complex nature, suggesting it encompasses several interrelated polarities under a broader, unified framework. This study aims to examine the underlying factor structure of key mentalization measures, with the objective of proposing an empirically grounded and comprehensive model applicable in both clinical and research settings. In addition, we provided normative data (percentile ranks) for each individual measure as well as for the extracted factors. A total of 1,190 Spanish adults from the general population (Mage = 34.38; 68.2% female) completed an online survey including the Interpersonal Reactivity Index, the Toronto Alexithymia Scale, the Reading the Mind in the Eyes Test, and the Mindful Attention Awareness Scale. Exploratory and confirmatory factor analysis of these instruments supported a two-factor solution, labelled Cognitive Mentalization and Emotional Mentalization. Furthermore, these dimensions contributed to a higher-order global factor, termed Mentalization. Overall, we observed small negative correlations with age, and women scored higher than men
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".