Could Fact-checks Intervene Directionally Motivated Reasoning and Mitigate Social Divisions? A Case Study in Hong Kong
Bibliographic record
Abstract
Abstract This study examined the effectiveness of fact-checking in reducing misperceptions held by people of two opposing camps in the Anti-Extradition Bill Movement in Hong Kong. The experimental design mirrored the political rhetoric in the city’s media and exposed participants to erroneous information in news reports that cast protesters in a negative light or accused the police unfoundedly. We found that directional motivation persistently exerted a profound influence on people’s acceptance of misinformation. Exposure to fact-checks was found to have limited effects in combating the influence of misinformation and mitigating social division. The effects were contingent on the audiences’ attitude strength and fact-checkers. The findings suggest that the effectiveness of fact-checking is subject to the political and media contexts in which misinformation and fact-checks are circulated as well as the implications of those contexts on people’s trust in fact-checks.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".