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ISSUES AND OUTCOMES IN STATE SUPREME COURT JUDICIAL REVIEW CASES

2000· article· en· W2009788905 on OpenAlexaboutno aff
Craig F. Emmert, Carol Ann Traut

Bibliographic record

VenueSoutheastern Political Review · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStatuteSupreme courtCivil libertiesLawPolitical scienceState (computer science)Quarter (Canadian coin)Government (linguistics)PoliticsHistory

Abstract

fetched live from OpenAlex

This paper examines the types of laws challenged and overturned in the supreme courts of all 50 states from 1981 through 1985. Major findings are that criminal statutes are challenged more frequently but overturned less often than other types of statues. Challenges to laws regulating economic activity account for just under a quarter of our cases and these laws are overturned over 20 percent of the time. Private cases, which make up about 14 percent of the data set result in invalidation about a fifth of the time. While there are fewer civil liberties and governmental cases, these cases result in laws being declared unconstitutional more frequently, over one‐third of the time. More specifically, death penalty laws are overturned in less than three percent of the cases in which they are challenged. On the other hand, cases involving statutes alleged to unconstitutionally discriminate and those regulating local government result in invalidation over half the time.

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)0.044
metaresearch head score (Gemma)0.181
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.181
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.010
Science and technology studies0.0060.004
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.051
GPT teacher head0.376
Teacher spread0.324 · 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 designObservational
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
Published2000
Admission routes1
Has abstractyes

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