Directed Forgetting and the Production Effect
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The item-based directed-forgetting effect is explained as a difference in how strongly people encode remember-cued over forget-cued targets. In contrast, the production effect is typically explained as a difference in the distinctiveness of the memory of produced over unproduced targets. The procedural alignment of the two effects - directing participants to remember or forget, produce or not - coupled with their different theoretical explanations (i.e., strength vs. distinctiveness) presents an opportunity to investigate common versus differential effects of elaborative encoding. This study aims to bridge the gap between these two well-established phenomena by comparing the differences in directed forgetting and the production effect in the context of recognition. Mixed- and pure-list designs were utilized to provide an index of each of these mechanisms in both procedures. Along with a standard production effect and directed forgetting effect in the mixed-list conditions, we found evidence for strength primarily driving results in both procedures. Results are explained using a global matching model of recognition memory, MINERVA 2, by assuming varying levels of encoding strength in relation to task demands. Critically, we obtain the best fit using a strength mechanism over a combined strength and distinctiveness mechanism for our data.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it