B - 70Memory for Neutral Memoranda: Reconsidering Salience Effects in Alexithymia
Bibliographic record
Abstract
Objective: Alexithymia is a personality trait characterized by difficulties in identifying feelings (DIF), describing feelings (DDF), and externally oriented thinking (EOT). Alexithymia has been associated with poorer memory specifically for emotive words and other memoranda and personally salient information. Yet, there is some indication of more generalized effects on various aspects of cognition. More, the literature is limited by studies with small samples. The objective of this study was to investigate alexithymia and memory for neutral words in a large sample. Method: Young adults (n = 297, age 18–39; 214 female) studied a neutral word list, performed recognition testing 1 hr later, and completed the Toronto Alexithymia Scale-20 (TAS-20). Results: Delayed recognition memory (d’) was correlated with sex (female>male) and Externally Oriented Thinking (EOT), but not age, Difficulty Identifying Feelings (DIF) or Difficulty Describing Feelings (DDF). Hierarchical regression on d’ was significant with sex (but not age) as a predictor in Step 1 (R2 = .022, p = .04; βsex = .43); and sex, DIF and EOT as predictors in Step 2 (R2 = .064, p = .002; R2change = .042, p = .005; βsex = .38, p = .03; p, βDIF = −.51, p = .03; βEOT = −.97, p = .002). Thus, poorer delayed neutral word memory in young adults was associated with male sex and higher DIF and EOT. Conclusions: Alexithymia may contribute to memory differences using neutral memoranda, suggesting more general effects on memory in alexithymia than are apparent in previous studies. That is, contextual and personal salience effects in alexithymia may be additive rather than exclusive in memory processing and retrieval. Further study is needed to clarify the direction and nature of these complex relationships.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".