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Record W3192522861

Dare to Diverge: Time for Administrative Law in Hong Kong to Stand on its Own Two Feet

2019· article· en· W3192522861 on OpenAlexaboutno aff
Stephen Thomson

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAppealLawTribunalEconomic JusticeCertaintyPolitical scienceEnglish lawAdministrative lawLegal certainty
DOInot available

Abstract

fetched live from OpenAlex

Hong Kong’s system of administrative law has drawn strength and durability from its English counterpart, on which it was heavily modeled. Too often, however, there is a slavish acceptance of the pre-eminence of English law and a tendency to conservativism and a lack of innovation. This article argues that Hong Kong courts and legislators must dare to diverge from English law where an alternative path would prove more credible or appropriate. Three prisms are deployed through which to argue that a misplaced emulation of English law can result in a poor legal framework. First, it is shown that a failure to properly conceptualize error of law as a ground of judicial review has resulted in a ground that, locally, is in a state of incoherence and disarray and that the admission or non-admission of a distinction between jurisdictional and non-jurisdictional errors urgently requires clarification from the Court of Final Appeal. Second, it is proposed that the English-inspired incorporation of a specific time limit in the rules for applying for judicial review should be abolished in the interests of access to justice and legal certainty, drawing on the experiences of jurisdictions such as New Zealand, Canada, and Scotland. Finally, it is explained why the antiquated system of administrative tribunals in Hong Kong, redolent of the unreformed English tribunal system of decades past, needs comprehensive structural and procedural redesign. Courts and legislators must dare to diverge in these areas, with Hong Kong’s administrative law standing on its own two feet, where minds are focused on a genuine, locally crafted improvement of standards prevailing in administrative law and public administration.

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)0.005
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0110.010
Scholarly communication0.0120.004
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.341
Teacher spread0.312 · 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 routes1
Has abstractyes

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