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Record W2523444495 · doi:10.5539/ass.v12n10p244

Political Regime Dynamics and Social Security Reform: A Case Study of the Social Security Act Amendments during the Periods of Yingluck and Prayuth

2016· article· en· W2523444495 on OpenAlexvenueno aff
Wichuda Satidporn

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSocial securityPoliticsLegislatureGovernment (linguistics)Social Security ActPublic administrationSocial policyWelfarePolitical economyPolitical scienceCoalition governmentEconomicsSociologyLaw

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.014
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.330
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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