Toward the Development of a New Self-Report Alexithymia Scale
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.
Bibliographic record
Abstract
Addressing methodological problems in the development of existing scales for measuring alexithymia, this study reports the development of a new self-report scale. The Toronto Alexithymia Scale (TAS) was devised with concern for theoretical congruence with the alexithymia construct, independence of social desirability response bias, and internal consistency. Initially, 41 items were administered to 542 college students. Twenty-six items meeting preestablished psychometric guidelines were retained. Factor analysis yielded four interpretable factors, all consistent with the construct. The scale demonstrated adequate split-half and test-retest reliability, and scores were not significantly associated with age, education, and socioeconomic status. These preliminary results suggest that the TAS may be used as a clinical screening device with psychiatric and general medical patient populations.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it