Flexible and rigid persistence: Relations with passion, vitality, and intention to stay in university teachers
Bibliographic record
Abstract
Passion and persistence are related constructs that have been perceived as key qualities for people to achieve their aims. While passion has been widely analyzed from a dualistic position, studies on persistence have rarely been focused on persistence regarding its quality. Thus, the aim of this study was twofold. Firstly, it aimed to analyze the relationships between flexible and rigid persistence, harmonious and obsessive passion, subjective vitality, and intention to stay in a sample of 201 university teachers from 20 universities. The secondary goal was to translate and assess the psychometric properties of the Spanish version of the Flexible and Rigid Persistence Scale. Overall, the findings supported the hypotheses tested. Regarding the first aim, we tested a structural equation model in which we hypothesized that harmonious passion would positively lead to flexible persistence and, to a lesser degree, to rigid persistence, and that obsessive passion would positively predict rigid persistence and negatively predict flexible persistence. In turn, both types of persistence would predict intention to continue teaching (activity outcome), but only flexible persistence would predict subjective vitality (life outcome). As expected, the structural equation model showed that harmonious passion for teaching predicted flexible persistence, while obsessive passion for teaching predicted rigid persistence and it was negatively related to flexible persistence. In turn, only flexible persistence predicted subjective vitality and intention to keep on teaching. Regarding the second goal of the study, results from exploratory structural equation modeling, reliability analysis, and multi-group exploratory structural equation modeling supported the psychometric properties of the Spanish version of the scale in the educational context for university teachers. These results are partially consistent with those reported in the original version, and they lead to new research on the role of passion and persistence in education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".