The Interaction Between the Production Effect and Serial Position in Recognition and Recall
Bibliographic record
Abstract
In memory tasks, items read aloud are better remembered than their silently read counterparts. This production effect is often interpreted by assuming a distinctiveness benefit for produced items, but whether this benefit also comes at a cost remains up for debate. In recall tasks, when pure lists are used in which all items are produced or read silently, studies have shown a better recall of produced items at the last serial positions, but a lower recall at the first positions. This cost of production has been interpreted by assuming that production interferes with rehearsal. However, in recognition tasks, models typically assume that the distinctiveness benefit for produced items comes at no cost. Across four experiments, participants completed a 2AFC recognition test, an old-new recognition test or an immediate serial recall test. List length was also manipulated. Results show that although the production effect is larger at the last serial positions, the cross-over interaction between the production effect and serial position observed in recall was not present in recognition. These results suggest that task-related differences in the production effect may inform us about the modulation of basic memory processes by task demands.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".