Subjective Well-Being in Cities: A multidimensional concept of individual, social and cultural variables
Bibliographic record
Abstract
Subjective indicators of well-being have been proposed as guides for development policy since development is not limited to material wealth. Development studies have suffered from a materialistic bias . The paper presents a comparative cross-cultural investigation of domains of subjective well-being (SWB) and a global measure of Satisfaction with Life as a Whole (SWLS) in three cities: Bogotá-Colombia; Belo-Horizonte-Brazil and Toronto-Canada. The Personal and National Wellbeing Indexes (PWI and NWI) developed by the International Wellbeing Group as well as the Satisfaction With Life Scale were applied and successfully validated at the city level. The cities chosen have similar democratic institutions but different cultures and different ¿objective¿ indicators of development. Significant differences across cities as well as significant interaction effects were found for the subjective well-being indexes and demographic variables. Based on these results, we propose that NWI may be seen as a contextual antecedent of PWI, consistent with our view that individual evaluations of SWB may be determined by dispositional factors (top-down), context (bottom-up domains) and cultural values. The validation of the subjective well-being indexes in diverse cultural contexts is an important contribution in a field that has been mainly dominated by European, American and Australian samples.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".