Directed forgetting meets the production effect: Distinctive processing is resistant to intentional forgetting.
Bibliographic record
Abstract
The production effect refers to the fact that, relative to reading a word silently, reading a word aloud during study improves explicit memory. The authors tested the distinctiveness account of this effect using the item method directed forgetting procedure. If saying words aloud makes them more distinctive, then they should be more difficult to forget on cue than should words read silently. Participants studied a list of words by reading half aloud and half silently; half of the words in each of these subsets were followed by a Remember instruction and half were followed by a Forget instruction. There was a robust production effect for both Remember and Forget words on an explicit recognition test. Critically, however, a directed forgetting effect was observed only for words read silently; words read aloud at study were unaffected by memory instruction. An implicit speeded reading test showed equal priming for all studied items. This pattern supports a distinctiveness account of the production effect: Words processed distinctively during production are not influenced by subsequent rehearsal differences.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".