The pursuit of self-interest: Self-interest bias in attitude judgment and persuasion.
Bibliographic record
Abstract
Self-interest affected the direction of attitudes in 4 studies exploring attitude judgment and persuasion. Experiment 1 showed that both self-interest and symbolic concerns predicted attitudes. The biasing role of self-interest in producing the well-known persuasion effects of personal relevance and argument strength was examined by disentangling the competing effects of personal costs and benefits. Experiment 2 used a standard personal relevance manipulation in the absence of supportive arguments and showed that perceptions of personal costs associated with the advocated policy partially mediated its negative effects on attitudes. Experiments 3 and 4 independently manipulated the onset of personal costs associated with an issue and the onset of issue-related benefits conveyed by supportive arguments. Postmessage attitudes were an additive function of personal costs and argument-specified benefits, and perceived costs and benefits biased information processing in a self-interested manner. A revised conception of personal relevance and argument strength is discussed.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".