The Trajectory of Targets and Critical Lures in the Deese/Roediger–McDermott Paradigm: A Systematic Review
Bibliographic record
Abstract
The Deese/Roediger-McDermott (DRM) paradigm has been used extensively to examine false memory. During the study session, participants learn lists of semantically related items (e.g., pillow, blanket, tired, bed), referred to as targets. Critical lures are items which are also associated with the lists but are intentionally omitted from study (e.g., sleep). At test, when asked to remember targets, participants often report false memories for critical lures. Findings from experiments using the DRM show the ease with which false memories develop in the absence of suggestion or misinformation. Given this, it is important to examine factors which influence the generalizability of the findings. One important factor is the persistence of false memory, or how long false memories last. Therefore, we conducted a systemic review to answer this research question: What is the persistence of false memory for specific items in the DRM paradigm? To help answer this question our review had two research objectives: (1) to examine the trajectory of target memory and false memory for critical lures and (2) to examine whether memory for targets exceeded false memory for critical lures. We included empirical articles which tested memory for the same DRM lists with at least two testing sessions. We discuss the results with respect to single-session delays, long-term memory recall and recognition, remember and know judgments for memory, and the effect of development, valence, warning, and connectivity on the trajectory of memory. Overall, the trajectory of targets showed a relatively consistent pattern of decrease across delay. The trajectory of critical lures was inconsistent. The proportion of targets versus critical lures across delay was also inconsistent. Despite the inconsistencies, we conclude that targets and critical lures have a dissimilar trajectory across delay and that critical lures are more persistent than targets. The findings with respect to long-term recall and recognition are consistent with both Fuzzy Trace Theory and Associative-Activation Theory of the DRM effect. The generation of false memory with brief delays (3-4 s) is better explained by Associative-Activation Theory. Examining the connectivity between target items, and critical lures, and the effect that has during study and retrieval, can provide insight into the persistence of false memory for critical lures.
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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 | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".