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Record W4395058870 · doi:10.29173/alr2734

Exploring the Role of Mandatory Mediation in Civil Justice

2023· article· en· W4395058870 on OpenAlexaffvenue
Nayha Acharya

Bibliographic record

VenueAlberta Law Review · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMediationEconomic JusticeCriminologyPolitical scienceLawLaw and economicsBusinessSociology

Abstract

fetched live from OpenAlex

In this article, I offer a framing of the debates around mandatory mediation that rest on the premise that a legitimate civil justice process depends on unhindered access to an adjudicative system, which must be recognized as a procedural right. This is a keystone of the rule of law, and a valid legal system that deserves the authority that it asserts is contingent on this. My central thesis is that requiring mediation (which is independent of the rule of law) before allowing full access to adjudication compromises the procedural rights of legal subjects, and the rule of law principle. Such a mandate is, therefore, an improper exercise of legal authority. This does not, however, mean that mediation cannot have significant value in enhancing the civil justice commitment to human dignity. The benefits that abound in mediation should be widely accessible, especially because mediation can (when it functions well) offer autonomous, empowered decision-making. The analyses that I offer here pave the road for determining, pragmatically, how mediation should be incorporated into civil justice systems, such that individuals can have legal claims adjudicated in a system that centralizes the rule of law and may also choose an equitable and well-structured mediation system that is responsive to concerns raised by critical race and feminist scholars about informal dispute resolution.

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)0.030
metaresearch head score (Gemma)0.039
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: none
Teacher disagreement score0.030
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.039
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.032
Scholarly communication0.0100.017
Open science0.0040.010
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0090.001

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 head0.049
GPT teacher head0.254
Teacher spread0.205 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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