Passion: Does one scale fit all? Construct validity of two-factor passion scale and psychometric invariance over different activities and languages.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The passion scale, based on the dualistic model of passion, measures 2 distinct types of passion: Harmonious and obsessive passions are predictive of adaptive and less adaptive outcomes, respectively. In a substantive-methodological synergy, we evaluate the construct validity (factor structure, reliability, convergent and discriminant validity) of Passion Scale responses (N = 3,571). The exploratory structural equation model fit to the data was substantially better than the confirmatory factor analysis solution, and resulted in better differentiated (less correlated) factors. Results from a 13-model taxonomy of measurement invariance supported complete invariance (factor loadings, factor correlations, item uniquenesses, item intercepts, and latent means) over language (French vs. English; the instrument was originally devised in French, then translated into English) and gender. Strong measurement partial invariance over 5 passion activity groups (leisure, sport, social, work, education) indicates that the same set of items is appropriate for assessing passion across a wide variety of activities--a previously untested, implicit assumption that greatly enhances practical utility. Support was found for the convergent and discriminant validity of the harmonious and obsessive passion scales, based on a set of validity correlates: life satisfaction, rumination, conflict, time investment, activity liking and valuation, and perceiving the activity as a passion.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.019 | 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 it