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Record W3115341218 · doi:10.5539/jpl.v14n2p27

Comparative Judicial Emergency Administration during Pandemic Covid-19

2020· article· en· W3115341218 on OpenAlexvenueno aff
Ibnu Sina Chandranegara

Bibliographic record

VenueJournal of Politics and Law · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Policy Analysis in Indonesia
Canadian institutionsnot available
Fundersnot available
KeywordsLegislatureDecreeState of emergencyDelegationPolitical scienceAdministration (probate law)LawPandemicConstitutional courtNoveltyState (computer science)BusinessCoronavirus disease 2019 (COVID-19)Public administrationConstitutionMedicinePsychologyPolitics

Abstract

fetched live from OpenAlex

The Decree of a state of emergency affects not only the executive and legislative branches but also the judiciary. The Covid-19 Pandemic in various countries has both direct and indirect effects on the judiciary, especially in the performance of its duties and functions. This article is to found out the answer of two research question first, how court administration in the United States and Indonesia responds to the Covid-19 pandemic emergency and second, how is its reflection in on optimizing access to justice for court administration even under in the state of emergencies to the pandemic Covid -19. This study uses the comparative method by a study on legal material and practice of judicial emergency in other countries to take the best material and approach to provides advice that needs to be avoided in Indonesian Judiciary. This article has a novelty that legal material in the Judiciary act and procedural law books so limiting delegation to set supplementary regulations for each court and creating potential uniformity for emergency policy in the judiciary.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.092
GPT teacher head0.402
Teacher spread0.310 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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