Reducing the Misinformation Effect Through Initial Testing: Take Two Tests and Recall Me in the Morning?
Bibliographic record
Abstract
Initial retrieval of an event can reduce people's susceptibility to misinformation. We explored whether protective effects of initial testing could be obtained on final free recall and source-monitoring tests. After studying six household scenes (e.g., a bathroom), participants attempted to recall items from the scenes zero, one, or two times. Immediately or after a 48-hour delay, non-presented items (e.g., soap and toothbrush) were exposed zero, one, or four times through a social contagion manipulation in which participants reviewed sets of recall tests ostensibly provided by other participants. A protective effect of testing emerged on a final free recall test following the delay and on a final source-memory test regardless of delay. Taking two initial tests did not increase these protective effects. Determining whether initial testing will have protective (versus harmful) effects on memory has important practical implications for interviewing eyewitnesses.
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How this classification was reachedexpand
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 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".