Item-specific and relational processing both improve recall accuracy in the DRM paradigm
Bibliographic record
Abstract
Using the Deese-Roediger-McDermott (DRM) paradigm, Huff and Bodner found that both item-specific and relational variants of a task improved correct recognition, but only the item-specific variants reduced false recognition, relative to a read-control condition. Here, we examined the outcome pattern when memory was tested using free recall, using the same item-specific versus relational task variants across three experiments as our previous study (processing instructions, pleasantness ratings, anagram generation). The outcome pattern in recall was similar to recognition, except relational processing at study actually reduced the DRM illusion, though not as much as item-specific processing. To reconcile this task difference, we suggest that the memory information laid down during relational encoding enhances the familiarity of the critical items at test. To the extent that familiarity is used less as a basis for responding in free recall than in recognition, relational processing ironically reduces rather than increases the DRM illusion in recall.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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".