The Relationship between Resilience, Psychological Hardiness, Spiritual Intelligence, and Development of the Moral Judgement of the Female Students
Bibliographic record
Abstract
This study aims to determine the relationship between resilience, psychological hardiness, spiritual intelligence, and development of the moral judgment of the female students in 2014. The research sample included 200 female high school students of District 2, Ahvaz-Iran in educational year of 2014-15 that were selected using the available sampling method. In this paper, for measuring the resilience, psychological hardiness, and spiritual intelligence, resilience scale, Ahvaz Hardiness questionnaire, and moral judgment questionnaire were used, respectively. For data analysis, in addition to the descriptive statistics, inferential statistical such as Pearson's correlation coefficient and multivariate regression analysis using the simultaneous method was used. Data analysis showed that there is a positive and significant relationship between the psychological hardiness, spiritual intelligence, and growth of the moral judgment. Moreover, results of the regression analysis showed that predictor variables are effective in clarifying the 0.41 of the variance of the spiritual intelligence development of the students.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".