MétaCan
Menu
Back to cohort
Record W2612301594 · doi:10.4324/9781315400068

Debating Judicial Appointments in an Age of Diversity

2017· book· en· W2612301594 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)Political sciencePsychologyLaw

Abstract

fetched live from OpenAlex

What should be the primary goals of a judicial appointments system, and how much weight should be placed on diversity in particular? Why is achieving a diverse judiciary across the UK taking so long? Is it time for positive action? What role should the current judiciary play in the appointment of our future judges?
\nThere is broad agreement within the UK and other common law countries that diversity raises important questions for a legal system and its officials, but much less agreement about the full implications of recognising diversity as an important goal of the judicial appointments regime. Opinions differ, for example, on the methods, forms, timing and motivations for judicial diversity. To mark the tenth anniversary of the creation of the Judicial Appointments Commission (JAC) in England and Wales, this collection includes contributions from current and retired judges, civil servants, practitioners, current and former commissioners on the JAC and leading academics from Australia, Canada, South Africa and across the UK. Together they provide timely and authoritative insights into past, current and future debates on the search for diversity in judicial appointments.
\nTopics discussed include the role and responsibility of independent appointment bodies; assessments of the JAC’s first ten years; appointments to the UK Supreme Court; the pace of change; definitions of ‘merit’ and ‘diversity’; mandatory retirement ages; the use of ceiling quotas; and the appropriate role of judges and politicians in the appointments process.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.607
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.333
Teacher spread0.241 · 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
GenreOther

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

Citations22
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicJudicial and Constitutional StudiesFrench-language works237,207