The production effect in recognition memory: Weakening strength can strengthen distinctiveness.
Bibliographic record
Abstract
Producing items (e.g., by saying them aloud or typing them) can improve recognition memory. To evaluate whether production increases item distinctiveness and/or memory strength we compared this effect as a function of the percentage of items that participants typed at encoding (i.e., 0%, 20%, 50%, 80%, and 100%). Experiment 1 revealed a strength-based pattern: The production effect was similar across pure-list (i.e., 0% vs. 100%) and mixed-list (i.e., 20%, 50%, 80%) designs, and there was no observed influence of statistical distinctiveness (i.e., 20% vs. 80%). In Experiment 2, we increased the study time for unproduced items to minimise the strength difference between produced and unproduced items. The manipulation attenuated the pure-list effect without eliminating the mixed-list effect, providing support for the inference that the mixed-list effect reflects distinctiveness. An influence of statistical distinctiveness also emerged: The mixed-list effect was larger when participants produced only 20%, rather than 80%, of the items. These findings suggest that both strength and distinctiveness contribute to the production effect in recognition. (PsycINFO Database Record
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".