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Record W2020681074 · doi:10.14507/epaa.v20n40.2012

Developmental State Policy, Educational Development, and Economic Development: Policy Processes in South Korea, 1961-1979

2012· article· en· W2020681074 on OpenAlexaff
Ki Su Kim

Bibliographic record

VenueEducation Policy Analysis Archives · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Industrial and Economic Development
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDevelopmental stateHuman capitalState (computer science)LegitimacyEconomic growthEducation policyPolitical scienceEconomicsSociologyHigher educationPoliticsLaw

Abstract

fetched live from OpenAlex

This paper explores two inter-connected issues – the state’s role in educational development and educational contribution to economic development – in the policy processes entailed by the South Korean state’s pursuit of economic development during the Park Chung Hi era, 1961-1979. It disputes the statist view that South Korea’s economic development was the outcome of a strong state’s imposition of developmental policies. It also denies the human capital account that central to the South Korean state’s education policy was the skills formation agendum. In this paper’s process analysis, educational contribution to economic development was made most importantly in the entrance competition-swept schools by virtue of their equipping South Koreans with basic knowledge and intellectual skills and the most important educational asset for economic development was those schools’ explosive growth. The latter took place as an unexpected effect of the state’s developmental policy of containment which aimed to secure scarce funds for strategic developmental projects. This policy intensified entrance competitions, boosted demand for education, and provoked public call for state commitment to educational expansion. The legitimacy-deficient regime responded politically and compromised on the developmental education policy from one level of formal schooling to another. The image of the developmental state thus portrayed is quite contrary to that provided by the statist-human capital perspective.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.005
Scholarly communication0.0060.004
Open science0.0000.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.318
Teacher spread0.289 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2012
Admission routes1
Has abstractyes

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