Production does not improve memory for face–name associations.
Bibliographic record
Abstract
Strategies for learning face-name associations are generally difficult and time-consuming. However, research has shown that saying a word aloud improves our memory for that word relative to words from the same set that were read silently. Such production effects have been shown for words, pictures, text material, and even word pairs. Can production improve memory for face-name associations? In Experiment 1, participants studied face-name pairs by reading half of the names aloud and half of the names silently, and were tested with cued recall. In Experiment 2, names were repeated aloud (or silently) for the full trial duration. Neither experiment showed a production effect in cued recall. Bayesian analyses showed positive support for the null effect. One possibility is that participants spontaneously implemented more elaborate encoding strategies that overrode any influence of production. However, a more likely explanation for the null production effect is that only half of each stimulus pair was produced-the name, but not the face. Consistent with this explanation, in Experiment 3 a production effect was not observed in cued recall of word-word pairs in which only the target words were read aloud or silently. Averaged across all 3 experiments, aloud targets were more likely to be recalled than silent targets (though not associated with the correct cue). The production effect in associative memory appears to require both members of a pair to be produced. Surprisingly, production shows little promise as a strategy for improving memory for the names of people we have just met. (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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".