Social policies in democratic and authoritarian regimes: comparing the introduction and implementation of the National Rural Employment Guarantee in India and Dibao in China
Bibliographic record
Abstract
Abstract Research on the welfare state often examines social policies in democratic regimes separately from social policies in authoritarian regimes. Two bodies of research have emerged, as the extant literature views these political systems as sufficiently distinct to merit the division of analysis. In this article, we challenge the existing approach by showing that differing regime types can indeed be analysed together. By looking for patterns of similarities, rather than differences, we bring the two literatures into conversation and show how a common factor can trigger social policy expansion in both regime types. Using case studies of India and China, the two most populous democratic and authoritarian regimes, this article illustrates how the expansion of policies that serve low-income groups – India’s Mahatma Gandhi National Rural Employment Guarantee (NREGA) and China’s Minimum Livelihood Guarantee Scheme (dibao) – were both prompted by social mobilisation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".