Reassessing the basis of the production effect in memory.
Why this work is in the frame
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Bibliographic record
Abstract
The production effect refers to a memory advantage for items studied aloud over items studied silently. Ozubko and MacLeod (2010) used a list-discrimination task to support a distinctiveness account of the production effect over a strength account. We report new findings in this task--including negative production effects--that better fit with an attributional account of this task. According to the attributional account, list judgments are influenced by recognition memory, knowledge of the composition of the 2 lists, and a bias to attribute non-recognized items to the 1st list. Using a recognition task to eliminate these attributional influences revealed production effects consistent with either a distinctiveness or strength account. In our discussion, we consider whether the absence of production effects on implicit-memory tests and in between-group designs provides unequivocal support for a distinctiveness account over a strength account.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it