MétaCan
Menu
Back to cohort
Record W2044630453 · doi:10.1017/s0008423907070242

Courts and Federalism: Judicial Doctrine in the United States, Australia, and Canada

2007· article· en· W2044630453 on OpenAlexaffabout
Anna Lennox Esselment

Bibliographic record

VenueCanadian Journal of Political Science · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsFederalismDoctrinePolitical scienceJurisprudenceLawSeparation of powersJudicial reviewMainstreamJudicial opinionLaw and economicsPoliticsSociology

Abstract

fetched live from OpenAlex

Courts and Federalism: Judicial Doctrine in the United States, Australia, and Canada , Gerald Baier, Vancouver and Toronto: UBC Press, 2006, pp. 207. Is everything old new again? Gerald Baier's insightful book brings back into the mainstream a long neglected examination of federalism from the perspective of judicial review. His analysis of the courts' impact on the development of federalism involves a detailed study of division of powers jurisprudence in the United States, Australia, and Canada. In each of these countries, Baier argues, the decisions of the highest courts continue to affect the shape of federalism, but his central claim turns on how these decisions are made. For Baier, judicial doctrine plays a significant role in influencing the reasoning of the courts and must be considered an independent variable worthy of study in its own right. Many scholars have debated the significance of doctrine on judicial decision making. However, Baier takes issue with scholars who, on the one hand, have characterized doctrine as a tool of objectivity and certainty, and those, on the other hand, who view doctrine as entirely political in nature (27). For Baier, doctrine is neither of these but it is “distinctly legal in character” and it is this legal reasoning that shapes outcomes (27).

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
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 head0.034
GPT teacher head0.314
Teacher spread0.280 · 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
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

Citations21
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Political ScienceSame topicJudicial and Constitutional StudiesFrench-language works237,207