Profiling misinformation susceptibility
Bibliographic record
Abstract
The global spread of misinformation poses a serious threat to the functioning of societies worldwide. But who falls for it? In this study, 66,242 individuals from 24 countries completed the Misinformation Susceptibility Test (MIST) and indicated their self-perceived misinformation discernment ability. Multilevel modelling showed that Generation Z, non-male, less educated, and more conservative individuals were more vulnerable to misinformation. Furthermore, while individuals' confidence in detecting misinformation was generally associated with better actual discernment, the degree to which perceived ability matched actual ability varied across subgroups. That is, whereas women were especially accurate in assessing their ability, extreme conservatives' perceived ability showed little relation to their actual misinformation discernment. Meanwhile, across all generations, Gen Z perceived their misinformation discernment ability most accurately, despite performing worst on the test. Taken together, our analyses provide the first systematic and holistic profile of misinformation susceptibility.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".