The Relationship between Optimism-Pessimism and Personality Traits among Students in the Hashemite University
Bibliographic record
Abstract
This study aimed to examine the correlation between optimism - pessimism and personality traits (extraversion, introversion, emotional stability and neuroticism), also aimed to identify the prevalence of optimism and pessimism in the study sample according to the variable sex, academic specialization, level of study, and grade point average. The study sample consisted of (534) students among undergraduate students enrolled in the Hashemite University during the summer semester 2010/2011. Results of study revealed that: A positive correlation relationship and statistically significant between optimism and introversion. Statistically significant positive correlation relationship between pessimism emotional equilibrium, and the pessimism emotion. Statistically significant negative correlation relationship between pessimism and extraversion, and between pessimism and introversion. Differ in the prevalence of optimism in three levels (high, moderate, and low) according to the variables sex, area of study, level of study, and grade point average. Different ratios of the three levels is widespread pessimism (high, moderate, and low) according to the variables sex, area of study, level of study, and grade point average. Statistically significant differences between males and females in the prevalence of trait optimism in favor of male students. The differences are statistically significant at the level of significance (0.05) between the academic level (first, second, third, and fourth) in the trait of optimism for the benefit of students who are in the level of the first, second, and third year. The presence of significance interaction between sex and grade point average on a feature of pessimism. The presence of significance interaction between specialization and grade point average on a feature of pessimism.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".