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Record W2948820973

L’encadrement constitutionnel de la révision des circonscriptions électorales - Étude de droit comparé

2016· dissertation· fr· W2948820973 on OpenAlexaboutno aff
Guillaume Fichet

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2016
Typedissertation
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceSuffrageConstitutionPhilosophyPoliticsLaw
DOInot available

Abstract

fetched live from OpenAlex

In the framework of representative democracies, the electoral redistricting aims to give jurisdiction to the election of members of parliamentary assemblies. Far from being a neutral and purely administrative measure, as evidenced by the tormented history of gerrymandering, this operation has many consequences on the fairness of election results, the balance of power between political parties, the formation of governmental majorities, and furthermore on the representation of interests, ideas, and values. In connection with the ongoing evolution of mentalities, the principles guiding the implementation of electoral constituencies are experiencing, in the continuity of secular change of government forms, a new metamorphosis tending to bring the people and the government closer together, so as to ultimately reach citizens’ expectations. Thus, electoral districts are expected to be in line with a more ambitious vision of equal representation, which requires not only voting equality but also effective representation and delimitation of parliamentary constituencies subtracted from pressures of political power. This trend, which is common to several legal systems, opens the way for a comparative study focused on four countries with different electoral traditions: the United Kingdom, Canada, the United States of America, and France. Beyond conventional opinions, it will be possible, at the intersection of law and politics, to bring out the many implications that these mutations induce on the consistency of electoral constituencies, on the nature of political representation and, ultimately, on the strengthening and renewal of democracy.

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)0.034
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.085
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.006
Science and technology studies0.0080.008
Scholarly communication0.0190.008
Open science0.0020.004
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0150.003

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 head0.057
GPT teacher head0.337
Teacher spread0.281 · 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 designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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