Passionately motivated reasoning: Biased processing of passion‐threatening messages
Bibliographic record
Abstract
OBJECTIVE: When facing setbacks and obstacles, the dualistic model of passion outlines that obsessive passion, and not harmonious passion, will predict greater levels of defensiveness. Our aim was to determine whether these passion dimensions predicted defensiveness in the same way when confronted with threatening messages targeting the decision to pursue a passion. METHOD: Across four studies with passionate Facebook users, hockey fans, and runners (total N = 763), participants viewed messages giving reasons why their favorite activity should not be pursued. Participants either reported their desire to read the messages (Studies 1 and 2) or evaluated the messages after reading them (Studies 3 and 4). RESULTS: Harmonious passion consistently predicted higher levels of avoidance or negative evaluations of the messages. These responses were attenuated for participants who had previously affirmed an important value (Study 1), or who were told that they do not control the passions they pursue (Study 4). CONCLUSIONS: Harmonious passion entails a sense of autonomy and control over activity engagement, which usually leads to nondefensive behavior. However, this sense of control may elicit more defensive responses from more harmoniously passionate individuals when the decision itself to pursue an activity is under attack.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".