Alexithymia and Vocational Maturity
Bibliographic record
Abstract
Alexithymia refers to an individual's deficit in identifying and processing feelings, in distinguishing feelings from bodily sensations, and an externally oriented way of thinking. Alexithymia has been linked to lower scores on verbal, non-verbal and general intelligence tests (Lilly & Valdez, 2001). Other studies have shown that higher scores in alexithymia measures corresponded to lower scores in creativity (Zenasni & Lubart, 2009) and emotional intelligence (Coffey & Kerns, 2003). Little research has been found exploring alexithymia with vocational measures, such as vocational maturity. The latter has been defined as how well individuals are capable to manage the cognitive and affective tasks that are proper to his or her stage of career development (Super & Thompson, 1979). This research aims to verify the impact of alexithymia (measured by the Toronto Alexithymia Scale, TAS-20) on vocational maturity (measured by the Career Educational Questionnaire, CEQ). The sample consisted of 592 Brazilian university students, ages between 16 and 51 years old, of both sexes (M = 224; F = 368). Multiple regression analysis was conducted to evaluate how well the three dimensions of alexithymia measured by the TAS-20 (difficulty in describing feelings, difficulty in identifying feelings and external-oriented thinking) predicted the four dimensions of the vocational maturity measured by the CEQ (self-knowledge, information sources, career planning, decision factors and occupational knowledge). Results: using Bonferroni method the type I error was controlled. The determination coefficient (R2= .127) indicates that 13% of the variance of the decision factors (CEQ) is explained by the linear association with the difficulty in identifying feelings (TAS-20). Low scores on the decision factors (capacity to identify qualities and flaws of one's personality in order to choose a career) can be explained by a higher difficulty in identifying one's feelings.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".