The Role of Marital Status in Emotional Intelligence, Happiness, Optimism and Hope
Bibliographic record
Abstract
The role of marital status in emotional intelligence, happiness, optimism and hope was examined as well as the relationships between emotional intelligence, happiness, optimism and hope. The role of demographic factors was then considered in relation to these constructs. The participants included 500 individuals who were selected from Shiraz City; Fars province, Iran. A demographic questionnaire and five self-rating measures were used in this study. Married individuals demonstrated higher levels of “emotional intelligence,” “happiness,” and “trait/state hope” than widowed, divorced, single and remarried individuals. The “emotion attention” subscale of emotional intelligence was negatively correlated to “happiness,” “dispositional hope” and “state hope.” Emotional intelligence was found to correlate negatively to the “agency” factor of “state hope” on the “emotion clarity” subscale. Happiness correlated negatively with “optimism” and positively with “hope.” The roles of age, gender, occupation, level of education and ethnicity in the emotional intelligence, happiness, optimism, and trait and state hope were not significant.
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 | 0.003 |
| 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 | 0.001 | 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".