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Record W2111389223 · doi:10.5430/ijhe.v4n3p1

Internationalization, Deregulation and the Expansion of Higher Education in Korea: An Historical Overview

2015· article· en· W2111389223 on OpenAlexvenueno aff
Christopher Green

Bibliographic record

VenueInternational Journal of Higher Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Reforms and Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsInternationalizationDeregulationGovernment (linguistics)Quality assurancePolitical scienceHigher educationBusinessControl (management)Quality (philosophy)Economic growthInternational tradeEconomicsManagementMarketingMarket economyService (business)

Abstract

fetched live from OpenAlex

The purpose of this article is to provide an overview of internationalization policies in Korean higher education since 1993. Deregulation was a key strategy of Korean governments, but this strategy has led to an increasing oversupply of enrolment capacity. In response, the current government is implementing a system of reregulation to reduce the number of institutions and control admission quotas. Although cross-national comparisons put Korea’s schooling system among the world’s highest performing, deep structural and cultural challenges exist in higher education. The article recommends that future policy development and implementation should focus on three broad areas: 1) strengthening quality assurance; 2) increasing engagement with international bodies and networks; and 3) enforcing regulatory compliance.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.401
Teacher spread0.345 · 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

Citations44
Published2015
Admission routes1
Has abstractyes

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