Younger Adults Can Be More Suggestible than Older Adults: The Influence of Learning Differences on Misinformation Reporting
Bibliographic record
Abstract
ABSTRACT The aim of the present investigation was to determine whether differences in the strength of original information influence adult age differences in susceptibility to misinformation. One-half of the younger and older adults watched a slide sequence once (one-trial learning) that depicted a theft, whereas the remaining participants viewed the slide sequence repeatedly to ensure that all critical details were encoded (criterion learning). Three weeks later and immediately prior to final testing, participants were asked questions that contained misleading information. As expected, the degree of initial learning influenced age differences in misinformation reporting. That is, when event memory was poorer for older than younger adults (in the criterion learning condition), older adults were more susceptible to misinformation than younger adults. However, when memory of the event was poor (in the one-trial learning condition), the younger adults reported more misled details than the older adults, possibly because the younger adults had better memory for the misleading information. Therefore, strength of initial memory influences the extent and direction of adult suggestibility and helps explain the discrepancy found across studies in this area.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".