Bibliographic record
Abstract
Past work has demonstrated that drawing a sketch, compared to writing during encoding, improves memory of to-be-remembered words, pictures, and academic terms. We examined whether this benefit extended to emotional materials. In Experiment 1, negative, positive, and neutral words were presented in an encoding phase, with intermixed prompts to either write out or draw a picture representing the word. Participants later freely recalled words by writing them out. Recall was higher for words drawn than for words written at encoding, and the magnitude of the benefit was differentially enhanced for emotional compared to neutral words. In Experiment 2, negative, positive, and neutral words were again presented but encoding type was compared using pure lists between participants. The pattern of memory performance replicated that observed in Experiment 1. Further, the use of drawing as an encoding technique interacted with emotionality, whereby emotional words that were drawn were best remembered. Our results demonstrate that the memory benefit conferred by drawing at encoding extends to emotional materials. Our findings suggest that the use of drawing as an encoding strategy, and the emotionality of the stimulus itself, contributes independently to enhance retention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".