Bibliographic record
Abstract
Background: The social and economic woes that have inflicted many countries around the world are testimony to the inadequacy of current institutional makeup of societies where individualism and market forces by and large have taken the leading role in directing societies’ choices and resources. Problems of inequities in health and wealth, the widening gaps between the rich and the poor, employment insecurities, the growing social exclusion of the marginalized, and the looming environmental concerns are acute as ever. At the same time, the progressive social forces and the counter-balancing capacity of governments are being undermined by the prevailing neo-liberal forces. This sobering state of affairs can only lead to more problems and a growing frustration on the part of those who seek alternatives to the status quo, which have actually produced better results in certain countries. Objective: This study takes the position that the involvement of democratic collective institutions (e.g., local organizations and governments at all levels) in setting societal priorities and directing resources towards achieving those priorities would avoid or mitigate many of the socioeconomic problems facing us today. It aims to show that comprehensive social policy could prevent the emergence of such problems and contain the problems that remain, effectively working as a social vaccine. Methods: The study uses macroeconomic panel data and socioeconomic indicators from OECD countries to empirically examine the relationships between indicators of social wellbeing on the one hand, and measures of social policy on the other, while controlling for relevant macroeconomic covariates. Results: The empirical results indicate that better population health outcomes are consistently associated with stronger social policies, including social spending on health and non-health services. Also, they show lower poverty rate is associated with higher social spending. Lower crime rate is also associated with higher social spending, but it is strongly country-specific. Conclusion: Although improving social wellbeing and social protection are morally justified in their own right, the evidence presented in this study suggests that even a purely rational view concerned with the societal costs and benefits of public policy should find social policy an effective tool or vaccine against population ill-health, poverty, and crime.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".