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Record W6987971761

Voter Equality & Other Canadian Values: Finding the Right Balance

2011· article· en· W6987971761 on OpenAlexaboutno aff

Bibliographic record

VenueBerkley Law Scholarship Repository (University of California, Berkeley) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCompromisePrincipal (computer security)LegislationVotingLegislaturePopulationInequalityNorm (philosophy)House of Commons
DOInot available

Abstract

fetched live from OpenAlex

Representation by population (rep-by-pop) was one of the principal forces behind the creation of Canada and is a key pillar of democracy. Although some deviations from the norm of voter equality are acceptable, they should be grounded in principles that are widely accepted and viewed as legitimate. Canada’s federal electoral districts deviate from the rep-by-pop principle more than they ever have in our history. This is the result of Canada’s increasingly outdated rules and practices governing the distribution of seats in the House of Commons and our demographic changes. This problem is getting worse and, unless there is fundamental reform, will continue to do so in the future. Moreover, the character of voter inequality is changing. For decades, citizens in Alberta, Ontario, British Columbia, and urban centres have suffered from declining voting power. But in the face of massive immigration, the dilution of some Canadians’ votes and the amplification of others increasingly disadvantages Canadians from non-European backgrounds who are more likely to live in ridings with the largest populations. This Mowat Note identifies the constitutional, legislative and policy reasons why Canada so dramatically deviates from the principle of voter equality. It then explains if and how each of these factors can or should be addressed at present. It concludes with a proposed framework for a compromise piece of legislation that would deal with many, but not all, of the issues that produce such a skewed electoral map.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0350.012
Scholarly communication0.0110.002
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0170.002

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 head0.043
GPT teacher head0.254
Teacher spread0.211 · 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
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
Published2011
Admission routes1
Has abstractyes

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