Determinants of life satisfaction in Canada: A causal modeling approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Most research studies on Life Satisfaction/Subjective Wellbeing (SWB) have focused on one main determinant and a variety of social demographic variables to delineate the determinants of life satisfaction. However, very few research studies examine life satisfaction from a holistic approach. The aim of this study was to utilize a holistic approach to construct a causal model and identify major determinants of life satisfaction. This study utilized data from the General Social Survey, with a sample size of 19,597. Several multiple regression models were run sequentially to estimate standardized path coefficients for the causal model. Overall, above average satisfaction with life was reported by Canadian respondents. Respondents who were female, younger, married, from high socioeconomic status background, born in Canada, very religious, and demonstrated high level of neighborhood interaction had greater satisfaction with life. Similarly, respondents had greater life satisfaction if they had better health, social contact, leisure activities, more time with family and friends, more enjoyment with volunteer activities, and a greater sense of belonging to the community. Our results suggest that a holistic approach is necessary for understanding the causal process of life satisfaction. A significant number of causal connections contradict some of the findings in literature today. We have provided some possible explanations for these anomalies and policy implications.
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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) | 0.001 | 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 it