Broadening the social investment agenda: The OECD, the World Bank and inclusive growth
Bibliographic record
Abstract
Towards the close of the 20th century, the idea of social investment gained purchase as a way to legitimise social policy as a productive contribution. For those in the North, social investment provided a new rationale to counter neoliberal attacks on the welfare state, while in the South, the idea caught on in the form of conditional cash transfers. The World Bank and Organisation for Economic Development and Cooperation (OECD) played key roles in the development and diffusion of the social investment agenda beginning in the mid-1990s. While hewing to a common core, their interpretations of social investment differed in important respects. The OECD sought to grapple with the emergence of more flexible, post-industrial labour markets, marked by growing precarity, dualisation and feminisation and focused on work–family balance as a solution while the Bank, focused on the South, emphasised social investment in very poor children to break the intergenerational cycle of poverty. In response to new pro-equality movements and intellectual research documenting the growth in inequality, however, a decade later, both organisations moved to incorporate a broader orientation, focused on the concept of ‘inclusive growth’. This article explores these developments.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".