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Record W4247101709 · doi:10.1017/9781108596268

Proportionality in Action

2020· book· en· W4247101709 on OpenAlexaboutno aff
Mordechai Kremnitzer, Talya Steiner, Andrej Lang

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsProportionality (law)Action (physics)Computer sciencePolitical scienceLawPhysics

Abstract

fetched live from OpenAlex

Proportionality in Action presents an empirical and comparative exploration of the proportionality doctrine, based on detailed accounts of the application of the framework by apex courts in six jurisdictions: Germany, Canada, South Africa, Israel, Poland and India. The analysis of each country is written and contextualized by a constitutional scholar from the relevant jurisdiction. Each country analysis draws upon a large sample of case law and employs a mixed methodological approach: an expansive coding scheme allows for quantitative analysis providing comparable and quantifiable measurements, which is enriched by qualitative analysis that engages with the substance of the decisions and captures nuance, contextualizing the data and providing it with meaning. The book concludes with a comparative chapter that synthesizes some of the most interesting findings. Focusing on deviations of the practice of proportionality from theory, the authors conclude their argument in support of an integrated approach to the application of proportionality.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.027
Scholarly communication0.0090.009
Open science0.0010.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0100.002

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 head0.113
GPT teacher head0.305
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations60
Published2020
Admission routes1
Has abstractyes

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