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Record W2903239299 · doi:10.1093/icon/moaa006

Shadow constitutional review: The dark side of pre-enactment political review in Ireland and Japan

2020· article· en· W2903239299 on OpenAlexaboutno aff
David Kenny, Conor Casey

Bibliographic record

VenueInternational Journal of Constitutional Law · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsConstitutionalismConstitutionalityPoliticsInstitutionJudicial reviewParliamentShadow (psychology)LawPolitical scienceConstitutional theoryConstitutional lawSociologyConstitutionLaw and economicsDemocracy

Abstract

fetched live from OpenAlex

Abstract Political constitutionalism is a major area of inquiry in contemporary constitutional discourse. A significant and increasingly central aspect of political constitutionalism is pre-enactment political review: laws being reviewed for constitutionality or rights compliance by parliament or the executive. This institution is said to be a good augmentation of, or even replacement for, the institution of judicial review, and it is said to bring with it a host of normative benefits. In this article, we wish to highlight an under-explored dark side to pre-enactment review. By undertaking a comparative analysis of functional pre-enactment review in several similar jurisdictions—Canada, New Zealand, and the UK—we contrast these systems, and the ordinary failings they display, with the much deeper problems of pre-enactment review in Ireland and Japan. These latter jurisdictions, we argue, not only fail to instantiate the benefits of pre-enactment review but in fact show that, in the right circumstances, pre-enactment review can have negative effects that are antithetical to the goals and values of political constitutionalism. We call this phenomenon “shadow constitutional review,” and suggest that it adds a layer of complexity and nuance to contemporary discussions of political constitutionalism.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.008
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 head0.030
GPT teacher head0.336
Teacher spread0.306 · 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.

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

Citations5
Published2020
Admission routes1
Has abstractyes

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