Latent structure of the alexithymia construct: A taxometric investigation.
Bibliographic record
Abstract
Despite a wealth of research on the validity of alexithymia and its association with a number of common medical and psychiatric disorders, the fundamental question of whether alexithymia is best conceptualized as a dimensional or categorical construct remains unresolved. In the current investigation, taxometric analysis is used to examine the nature of the latent structure of alexithymia. Several nonredundant taxometric procedures were performed with item sets from the 20-item Toronto Alexithymia Scale (R. M. Bagby, J. D. A. Parker, & G. J. Taylor, 1994) as indicators. These procedures were applied separately in large community (n = 1,933) and undergraduate (n = 1,948) samples and in a smaller sample of psychiatric outpatients (n = 302). The results across various taxometric procedures and the different samples provide strong support that alexithymia is a dimensional construct. Some theoretical implications of these findings for research on the alexithymia construct are discussed.
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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 | 0.012 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".