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Reimagining the Judiciary

2021· book· en· W4289718829 on OpenAlexaboutno aff
María C. Escobar-Lemmon, Valerie J. Hoekstra, Alice J. Kang, Miki Caul Kittilson

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceLaw and economicsLawSociology

Abstract

fetched live from OpenAlex

Abstract This book examines the factors that facilitate women’s representation on high courts worldwide. Diverse courts improve collective decision-making, strengthen public confidence in the judiciary and judicial decisions, and broaden access to the judicial process. Taken together, domestic and international factors explain women’s representation. These influences include judicial pipelines, domestic institutions including selection processes, and international expectations about gender equity. These explanations are evaluated using an original dataset, which includes both men and women appointed to high courts in all regions of the world. Pathways and processes are examined in-depth through five case studies: Canada, Colombia, Ireland, South Africa, and the United States. Taking a multi-method approach, the book combines insights from a cross-national, time-serial dataset with case studies drawing on fieldwork. Women are being appointed to high courts in greater numbers across every region of the world, and political and legal institutions provide context for where the gains are earliest and strongest. The findings suggest a chain of favorable promoters for women’s representation on high courts: new norms of gender equality encourage the reimagining of the judiciary; advocacy organizations challenge the status quo; and windows of opportunity enable change.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.321
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)0.0020.000

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 head0.038
GPT teacher head0.301
Teacher spread0.262 · 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 designNot applicable
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

Citations37
Published2021
Admission routes1
Has abstractyes

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