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Record W2589723758

Nom De Plume: Who Writes the Supreme Court's "By the Court" Judgments?

2016· article· en· W2589723758 on OpenAlexvenueno aff
Peter J. McCormick

Bibliographic record

VenueDalhousie law journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSupreme courtHumanitiesPolitical scienceRedactionLawSociologyPhilosophyTheology
DOInot available

Abstract

fetched live from OpenAlex

For several dozen of its major decisions, the Supreme Court in recent decades has adopted an unusual judgment style—the unanimous and anonymous “By the Court” format. Unlike judgments attributed to specific justices, “By the Court” presents an unusual and impersonal institutionalist face. But what is happening behind the facade? Are these deeply collegial products with the actual drafting divided between some (or most, or all) of the justices? Is it “business as usual” which for major judgments involves rotation between the senior judges? Or is it simply a pseudonym for the Chief Justice writing alone in an unusually emphatic way? Function word analysis is used to identify most likely authors for each “By the Court” decision; this provides a basis for understanding how Supreme Court practices for these important cases are evolving, and also carries implications for the likelihood of the current practice surviving the current Chief Justiceship. Au cours des dernieres decennies, dans un grand nombre de ses arrets, la Cour supreme a adopte une methode inhabituelle de redaction—ils sont signes de maniere unanime et anonyme par « la Cour. » Contrairement aux decisions signees par des juges, les arrets signes par la Cour presentent une facade inhabituelle et impersonnelle. Mais qu’y a-t-il derriere cette facade? Ces arrets sont-ils le produit d’un travail collectif, la redaction etant confiee a certains juges ou la plupart d’entre eux? Est-ce que les juges travaillent comme ils le font habituellement, ce qui signifie que la redaction des arrets marquants est confiee a tour de role aux juges ayant le plus d’anciennete? Ou est-ce simplement un pseudonyme pour la juge en chef qui redige seule avec une empathie inhabituelle? L’analyse des mots outils, ou mots fonctionnels, est utilisee pour determiner l’identite des auteurs les plus probables de chacun des arrets rendus par la Cour. Cette analyse donne un point de depart pour comprendre comment evoluent les pratiques de la Cour supreme pour ces affaires importantes. Elle souleve aussi la possibilite que la pratique actuelle survivra au depart de l’actuelle juge en chef.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.274
Teacher spread0.252 · 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
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
Published2016
Admission routes1
Has abstractyes

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