Benevolent Policies: Bureaucratic Politics and the International Dimensions of Social Policy Expansion
Bibliographic record
Abstract
Research on the welfare state has devoted considerable attention to social policy expansion. However, little is known about why governments expand social policies serving groups with limited power on issues with low visibility. I call these “benevolent policies.” This class of social policies improves population well-being but produces minimal political gains for the governments enacting them. Why do governments expand benevolent policies if political incentives for reform are weak? I investigate this question by focusing on government responses to malnutrition. Drawing on nine months of fieldwork, including 71 interviews, I argue that the origins of policy expansion can be found in the government bureaucracy. Bureaucrats with technical expertise—technocrats—can play a defining role, deploying international pressure to court executive support and orchestrate policy change. Their actions help explain the Indonesian government’s unexpected expansion of nutrition policies, which serve low-income women and children and address micronutrient malnutrition.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".