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MIXED AND HYBRID SYSTEMS OF JUSTICE AND THE DEVELOPMENT OF THE ADVERSARIAL PARADIGM: EUROPEAN LAW, INQUISITORIAL PROCESSES AND THE DEVELOPMENT OF COMMUNITY JUSTICE IN THE COMMON LAW STATES

2019· article· en· W2996061815 on OpenAlexaboutno aff
Tyrone Kirchengast

Bibliographic record

VenueRevista da Faculdade de Direito da UFMG · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Criminal Justice and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsAdversarial systemLawEconomic JusticeCommon lawPolitical science

Abstract

fetched live from OpenAlex

This article considers the movement away from traditional adversarial processes in common law jurisdictions by considering the influence of civil European law and procedure on the development of adversarial justice. It does this by first considering aspects of adversarial procedure that preclude alternative approaches to justice against the Framework Directives of the Council of Europe, the jurisprudence of the European Court of Justice and the European Court of Human Rights, and the practice and procedure of the International Criminal Court. Collectively, these European approaches demonstrate how mixed and hybrid adversarial-inquisitorial systems address the needs of trial participants in a participatory model of justice. The second part of this article considers the growth in interventionist problem-solving and community-based justice across four common law jurisdictions that traditionally identify as adversarial, namely the United States, Canada, England and Wales, and Australia. The rise of interventionist community courts in adversarial jurisdictions demonstrate that movement toward mixed and hybrid processes akin to the civil European experience is neither radical nor alternative, but rather supported by a line of domestic authority that for some time has recognised the benefits of alternative, inquisitorial and court supervised systems of justice.

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)0.001
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 score0.506
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.054
GPT teacher head0.302
Teacher spread0.249 · 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
Published2019
Admission routes1
Has abstractyes

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Same venueRevista da Faculdade de Direito da UFMGSame topicEuropean Criminal Justice and Data ProtectionFrench-language works237,207