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Record W4285162040 · doi:10.47348/salj/v139/i2a4

‘I beg to differ’: Are our courts too agreeable?

2022· article· en· W4285162040 on OpenAlexaboutno aff
Owen Rogers

Bibliographic record

VenueSouth African Law Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDissenting opinionDissentAppealLawPolitical scienceSupreme courtMajority opinion

Abstract

fetched live from OpenAlex

If dissenting judgments perform a valuable function in the administration of justice, too little dissent may indicate that the administration of justice is not reaping the benefits of dissent. South Africa belongs to the common-law tradition, which has always allowed dissenting judgments. The civil-law system traditionally did not, and this is still the position in many countries. In the modern era, considerations of transparency and accountability favour the disclosure and publication of dissenting judgments. Although they can play a role in the development of the law, their most valuable function is to improve the quality of judicial output by requiring majority judgments to confront the dissenting judgments’ reasoning. Factors which may affect the extent of dissent in appellate courts include case complexity and control over rolls; panel sizes; judicial diversity, personality and turnover; court leadership; research resources; modes of judicial interaction; and protocols on the timeliness of judgments. Data on dissent in South Africa’s Constitutional Court, Supreme Court of Appeal and Labour Appeal Court, as well as in the United Kingdom, Australia, Canada and the United States, suggest that there is less dissent in our intermediate appellate courts than might be expected. Changes in work procedures could yield a healthier pattern.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.994

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 studies0.0070.000
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 head0.030
GPT teacher head0.275
Teacher spread0.244 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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