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Record W4417285826 · doi:10.1080/08865655.2025.2599158

Balance of the Trade-off Between Accountability and National Security: A Case Study of Yonaguni Island, Okinawa, Japan

2025· article· en· W4417285826 on OpenAlexvenueno aff
Arata Hirai

Bibliographic record

VenueJournal of Borderlands Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityBalance (ability)Key (lock)

Abstract

fetched live from OpenAlex

This paper examines how the dysfunction of accountability mechanisms, caused by information asymmetry, hinders consensus-building among actors in the context of establishing NIMBYs with high levels of confidentiality and technical expertise. As a case study, this paper analyzes developments on Yonaguni Island, one of Japan’s border islands, regarding the invitation of the Japan Self-Defense Forces – a case that may be considered a deviation from conventional NIMBY issues. Initially, the local municipality and some residents of Yonaguni Island jointly invited the JSDF, and consensus was reached through a local referendum; however, after the establishment of the Camp, even some former proponents began to express doubts. This paper categorizes the relevant actors as those who impose accountability (holders) and those upon whom accountability is imposed (holdees), and analyzes the extent to which the duty of explanation has been fulfilled. The analysis shows that when a holdee responds to a holder’s request for explanation by providing information and fulfilling their explanatory duty, consensus-building is fostered; conversely, when sufficient information is not provided by the holdee to the holder, the resulting expansion of information asymmetry poses a risk of consensus breakdown.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.515
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.337
Teacher spread0.311 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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