Stronger Conspiracy Beliefs Are Associated With a Stronger Tendency to Act Dishonestly and an Overestimation of Others’ Dishonesty
Bibliographic record
Abstract
Conspiracy theories assert that others have engaged in dishonest actions. However, existing research indicates that individuals who believe in conspiracy theories may themselves be more inclined to engage in dishonest behavior. We conducted two preregistered studies—one in Turkey ( N = 706) and the other in Canada ( N = 835) and South Africa, ( N = 867)—testing the hypotheses that conspiracy beliefs would be positively correlated with (a) dishonest behavior during a monetary incentivized lying task and (b) overestimating the prevalence of dishonesty among other people. Overall, we found that stronger conspiracy beliefs were associated with higher dishonesty. Participants tended to overestimate dishonesty among their peers, but this tendency was significantly more pronounced among people with stronger conspiracy beliefs. Contrary to our hypothesis, country-level corruption did not moderate this association. These results shed light on the complex relationship between conspiracy beliefs, dishonesty, and expectations of dishonesty.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".