When passion makes the heart grow colder: The role of passion in alternative goal suppression.
Bibliographic record
Abstract
Quality of goal engagement and alternative goal suppression were investigated in this research. Integrating the dualistic model of passion (Vallerand et al., 2003) with goal-systems theory (Kruglanski et al., 2002), we hypothesized that obsessive passion--associated with recurrent goal-conflicts--would predict greater alternative goal suppression (i.e., goal-shielding) than would harmonious passion--characterized by effective synthesis of the passionate activity with other life domains. Results from 5 laboratory studies supported these hypotheses. In Study 1, participants' dispositional measures of harmonious and obsessive passion were correlated with an implicit measure of goal-shielding. Obsessive (but not harmonious) passion predicted the suppression of alternative goals and the progressive inhibition of unfamiliar goals. In Study 2, we extended these findings by demonstrating the interrelation between quality of goal engagement and goal-commitment such that goal-shielding effects were enhanced, but only for goals in conflict with other life domains (vs. well-integrated goals). In Study 3, the causal influence of passion on goal-shielding was supported via an experimental manipulation of passion. In Study 4, we replicated and extended Studies 1 and 3 by experimentally demonstrating that obsessive (but not harmonious) passion is a mindset conducive to the development of inhibitory links with alternative goals. Study 5 explored the psychological costs associated with repeated unconscious goal suppression by examining its effects on the depletion of self-regulatory resources. Collectively, the present results suggest that the qualitative distinction between obsessive and harmonious passion has implications for the goal-shielding effect and for subsequent self-regulatory behavior.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".