Psychometric properties and measurement invariance of the Rigid and Flexible Persistence Scale in a Brazilian professional sample
Bibliographic record
Abstract
Persistence involves the intention to maintain efforts when faced with obstacles and challenges, in order to achieve a specific goal. The Rigid and Flexible Persistence Scale (RFPS) is a self-report measure that assesses persistence that is theoretically derived from the premises of the Dualistic Model of Passion. The aim of the present research was to adapt the RFPS to Brazilian Portuguese and to estimate its evidence of validity and reliability in the context of work. Participants were 400 professionals, 55.8% women, aged between 18 and 68 years. The results indicate that the RFPS presented validity evidence based on the content. Corresponding to the theoretical expectations, exploratory and confirmatory factor analyses demonstrated adequacy of the structure composed of two factors, explaining 75% of the data variance, with good levels of reliability. The RFPS also revealed strong invariance across gender and work conditions (in-person vs remote). Flexible persistence showed positive association with harmonious passion and occupational self-efficacy. Conversely, rigid persistence showed positive association with obsessive passion. It was observed a mediational role of occupational self-efficacy in the relationship between harmonious passion and flexible persistence. Overall, the findings suggest that the RFPS is an adequate measure of persistence in a Brazilian occupational sample.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".