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Record W2107791665 · doi:10.1017/s1468109910000125

Political Science in Japan: Looking Back and Forward

2010· article· en· W2107791665 on OpenAlexaboutno aff
Takashi Inoguchi

Bibliographic record

VenueJapanese Journal of Political Science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsQuarter (Canadian coin)Political scienceBureaucracyEnlightenmentPolitical economyDemocracyNormativeVotingSociologyLawHistoryEpistemology

Abstract

fetched live from OpenAlex

Abstract The aim of the article is to review Japanese Political Studies in Japan (JPSJ) circa 2000 for the purpose of identifying the trends of JPSJ and gauging its scope, subject areas, and methods. I then identify the key questions asked in JPSJ, i.e. for the third quarter of the last century: (1) What went wrong for Japan in the 1930s and 1940s, which had been seemingly making progress in the scheme of ‘enlightenment and entrepreneurship’ and was ‘a rich country’ with a ‘strong army’? (2) What is the secret of Western democracy in excelling itself in terms of keeping freedom and accumulating wealth? For the last quarter of the last century: (1) Why is Japanese politics shaped so heavily by bureaucracy? (2) Why are its citizens so weakly partisan in their voting choice? (3) How are politics and economics intertwined in policy making and electoral behavior? Following these trends in JPSJ in the latter half of the last century, I identify the three trends that have emerged in the first quarter of this century: (1) historicizing the normative and institutional origins of Japanese politics, (2) putting Japanese politics in comparative perspective, (3) the new self-conscious impetus for data collection and theory construction. Despite the steady tide of globalization and the strong influence of American political science, market size, long tradition, and language facility, lead political scientists in Japan to think and write more autonomously.

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)0.007
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.015
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.358
Teacher spread0.337 · 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 designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

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