Political Regime Dynamics and Social Security Reform: A Case Study of the Social Security Act Amendments during the Periods of Yingluck and Prayuth
Bibliographic record
Abstract
According to previous studies on social security policy in Thailand, a causal link between elected governments and developments in social security has been observed in the direction that the initiation and implementation of social security policy (and perhaps all other social welfare policies) occurred more frequently and more successfully when this country was ruled by an elected government. However, this observation appears problematic when brought to bear on the most recent cases of social security reforms that have occurred, especially during the period under Yingluck Shinawatra government when the attempt to amend the 1990 Social Security Act proposed by the organized labor and 14,264 public petitioners was rejected by the directly-elected House of Representatives; and the period under Prayuth Chan-ocha government when the Social Security Act Amendments of 2015, which included many requests from organized labor mentioned in the rejected bill, was passed by the appointed National Legislative Assembly. Relying on a strategic-relational approach, this paper claims that the changes and continuities in the social security policy in each particular period did not occurred as simply a result of the different types of political regime but was part of a broader effort to deal with the tensions and conflicts between and within different sections of the bourgeoisie, political parties, state agencies, and working class over policy problems, solutions, and directions that have emerged as a result of Thailand’s capitalist transition during the past decade.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| 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".