Happiness and sense of community belonging in the world value survey
Bibliographic record
Abstract
People derive considerable social benefits from interacting with others that they encounter across a host of environmental domains: their city, region, country, continent, and even the world at large. We explore the extent to which perceived happiness hinges on one's sense of connection within each domain, drawing upon a large international sample of 120k respondents from 74 nations in the World Value Survey (2017–2020). This large battery of social and political attitudes includes items that ask: “tell me how close you feel to…” followed by each of city, region, country, continent, and the world. Options ranged from ‘very close’ to ‘not very close at all.’ Perceived happiness was scored on a 4-option item asking: “taking all things together, would you say you are…” with options ranging from ‘very happy’ to ‘not at all happy.’ After accounting for various demographic variables like age, sex, education, urban/rural environment, and income, results from a stepwise ordinal logistic regression analysis showed that one's perceived happiness was predicted by feeling connected to almost all domains; and the more connected one felt, the happier they were. One's connection however to region was not significant, wherein we suspect the item was too ambiguous for a clear response. Implications for overall wellbeing are discussed, as are directions for future research.
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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 | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".