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Record W2991392528 · doi:10.5509/2019924715

Development, Discernment, and Death: Dore on the South Korean Economy

2019· article· en· W2991392528 on OpenAlexaffvenue
Hyung‐Gu Lynn

Bibliographic record

VenuePacific Affairs · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Industrial and Economic Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDiscernmentCapitalismFutures studiesCapital (architecture)State (computer science)Developmental statePolitical scienceSociologyEconomyHistoryEconomicsLawPhilosophyEpistemologyAncient history

Abstract

fetched live from OpenAlex

Ronald Dore's 1977 article in Pacific Affairs , "South Korean Development in Wider Perspective," is a rare example of the scholar known for his writings on Japan applying his analytical lens on South Korea. What were some of this article's most notable areas of foresight and elision related to development studies? This essay answers this question by interpreting connections to publications before and after 1977 to analyze areas of insight under the rubric of "discernment" and overlooked subjects under "death." On one hand, Dore's essay was ahead of the curve in its deft foreshadowing of post-developmentalist, varieties of capitalism, and developmental state approaches to economic development. On the other, Dore sidestepped the effects of death on economic development in three forms: literal— effects of changing mortality rates on investments in education and human capital; industries related to death—wars, munitions production and arms expenditures; and the aftereffects of the death of a scholar—the revisiting and renewal of debates that can sometimes emerge as a result.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.023
Scholarly communication0.0070.009
Open science0.0010.005
Research integrity0.0010.004
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 head0.033
GPT teacher head0.230
Teacher spread0.198 · 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 designNot applicable
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

Citations0
Published2019
Admission routes2
Has abstractyes

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