Happiness Inequality Among a Sample of Iranian Older Population
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. This study evaluates the happiness inequality among older Iranians using concentration index analysis. A total of 739 people aged 60–90 years completed the Oxford Happiness Inventory (OHI) questionnaire. The SES variables were constructed using nonlinear principal component analysis (NLPCA) based on all related variables. The multivariate logistic regression analysis showed that persons in the SES quintiles 3–4, urban dwellers, literate, and with no underlying disease had higher odds of happiness than others. Based on the estimated concentration indices, there was inequality in happiness based on SES levels (concentration index [95% confidence Interval]: 0.14 [0.10, 0.19]; p < .05). Our results revealed that happiness in the older population was probably more prevalent among people with higher SES levels.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.004 | 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 it