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Record W2709722419 · doi:10.29173/alr1431

Reducing the Democratic Deficit: Representation, Diversity and the Canadian Judiciary, or towards a Triple P Judiciary

2000· article· en· W2709722419 on OpenAlexaffvenueabout
Richard Devlin, A. Wayne MacKay, Natasha Kim

Bibliographic record

VenueAlberta Law Review · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsDalhousie University
FundersU.S. Department of Justice
KeywordsDemocracyPoliticsLawDiversity (politics)StatuteJudicial independencePolitical scienceRepresentation (politics)Democratic deficitJudicial reviewJudicial discretionOpenness to experienceLaw and economicsSociologyPsychology

Abstract

fetched live from OpenAlex

The authors review the current structures for judicial appointments in Canada and provide statistical information about the results of these mechanisms in respect to diversity of representation on the courts. They are also critical of the fairness and openness of judicial appointments processes. After examining several variants of the dominant liberal view of law and of judges, the authors proffer and articulate a neo-realist theory of law and what they term a "bungee cord theory of judging." According to the former, law is inevitably a form of politics; according to the latter, judges are unavoidably political actors. In consequence, the judiciary is properly subject to democratic norms, including especially the norms of representation and of diversity. The authors then argue that, judged against those democratic norms, the present systems of judicial appointment (and the judiciary which it has put in place) suffers from what they term "a democratic deficit." After a detailed examination of past attempts to reform this system, of arguments for and against a more democratic and representational approach to judicial selection, and possible models of judicial selection, the authors propose their own reform: the establishment by statute of Judicial Appointments Commissions. Such an approach might help cure the democratic deficit and produce what they dub a Triple-P judiciary, that is, one that is politically accountable, professionally qualified, and proportionally representative.

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)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.511

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0090.018
Scholarly communication0.0070.003
Open science0.0020.002
Research integrity0.0020.003
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 head0.045
GPT teacher head0.303
Teacher spread0.257 · 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 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

Citations13
Published2000
Admission routes3
Has abstractyes

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