Money, sociability and happiness: are developed countries doomed to social erosion and unhappiness?
Bibliographic record
Abstract
Discovering whether social capital endowments in modern societies have been subjected or not to a process of gradual erosion is one of the most debated topics in recent economic literature. Inaugurated by Putnam’s pioneering studies, the debate on social capital trends has been recently revived by Stevenson and Wolfers (2008) contending Easterlin’s assessment. Present work is aimed at finding evidence for the relationship between changes in social capital and subjective well-being in eight European countries and in Japan between 1980 and 2005. In particular, I would like to answer questions such as: 1) is social capital in western Europe, Canada, Australia and Japan declining? Is such erosion a general trend of modern and richer societies or is it a characteristic feature of the American one? 2) can social capital trend help explain subjective well-being trend? In so doing, present research considers three different set of proxies of social capital controlling for time and socio-demographic aspects using WVS-EVS data between 1980 and 2005. My results are encouraging, showing evidence of positive correlation between several proxies of social capital and both happiness and life satisfaction. Furthermore, my results show that during last twenty-five years people in some of the most modern and developed countries have persistently lost confidence in the judicial system, religious institutions, parliament and civil service.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".