FALSE RECALL WITH THE DRMRS ('DRUMMERS') PROCEDURE: A QUANTITATIVE SUMMARY AND REVIEW
Bibliographic record
Abstract
In the Deese-Roediger-McDermott-Read-Solso (DRMRS) procedure, which has recently enjoyed widespread use, participants try to remember lists of items constructed around critical themes that are not presented. The purpose of this quantitative review was to estimate the extent to which these themes are falsely recalled (Critical Intrusions) and to compare this error rate with Correct Recall and with false recall of other words that were not presented (Noncritical Intrusions). Based on 111 estimates, the mean rate of Critical Intrusions was .374 (95% confidence interval of .344 to .403), which was a very large effect (d = 2.40). Critical Intrusions were less frequent than Correct Recall (.572) but more frequent than Noncritical Intrusions (.078). Critical Intrusions were lower (.318) for people told to be confident (not to guess) than for people not so cautioned (.428), a medium to large effect size (d = 0.69). Effects of other variables are summarized, and the theoretical and applied implications of these results are discussed.
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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 | 0.056 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".