Valence does not affect serial recall.
Bibliographic record
Abstract
Despite being the prototypical test of short-term/working memory, immediate serial recall is affected by numerous lexical and long-term memory factors. Within this large literature, very few studies have examined whether performance on the task is affected by valence, the extent to which a word is viewed as positive or negative. Whereas the NEVER model (Bowen, Kark, & Kensinger, 2018) makes the general prediction that negative words will be remembered better than positive words, two previous studies using serial recall have reported that positive words are better remembered than negative words. Three experiments reassessed whether valence affects immediate serial recall using stimuli equated on multiple dimensions, including both arousal and dominance. Over the 3 experiments, with 3 different sets of stimuli, we found no differences in either accuracy or various error measures as a function of valence. The data suggest that there is no effect of valence on an immediate serial recall task when potentially confounding dimensions are controlled. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".