WELCOME TO THE CITY: WHAT CAN URBAN CENTERS LEARN FROM RURAL/REMOTE EXPERIENCES WITH TELEPSYCHIATRY?
Bibliographic record
Abstract
According to Dieneru2019s tripartite model of subjective well-being (SWB), SWB is a complex and multifaceted phenomenon that captures both cognitive (life satisfaction) and affective (positive and negative affect) evaluations of oneu2019s life. However, little consensus has been achieved to date regarding the structure of SWB. A large number of studies have been conducted from a variable-centered perspective, whereas only a handful of studies have investigated how SWB components are organized within individuals. However, the variable-centered approach is based on a dubious assumption about prototypical patterns between components, which neglects the possibility that SWB components can be organized within individuals in a more complex manner. The aim of this study was to investigate SWB structure using person-centered approach and to examine the differences between SWB configurations. The sample included 2369 participants from MIDUS Survey. Participants completed the measures of positive and negative affect, life satisfaction, extroversion, neuroticism, optimism, and number of life events. Using a latent profile analysis, five distinct configurations of SWB were identified: high SWB, medium-high SWB, low SWB, and two incongruent profiles with moderate levels of affective well-being and extremely high or extremely low life satisfaction. The results showed that each SWB configuration demonstrated a unique pattern of associations with SWB determinants, but they also revealed some similarities between profiles. High and low life satisfaction profiles experienced a different number of life events, but they reported similar levels of dispositional traits. Low SWB and low life satisfaction profiles experienced similar number of life events, but low SWB profile had higher neuroticism and lower extroversion. Theoretical implications of the findings will be discussed.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".