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Record W7132898398

Federal electoral district inequality, the Saskatchewan Reference and Mixed Member Proportional representation (MMP)

2007· dissertation· W7132898398 on OpenAlexaboutno aff
Daniel Gold

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsProportional representationDisadvantagedRepresentation (politics)Electoral geographyDemocracyMandateGovernment (linguistics)IdeologySupreme court
DOInot available

Abstract

fetched live from OpenAlex

This paper criticizes the 1991 Supreme Court decision in Reference re Prov. Electoral Boundaries (Sask.), which held that the electoral map did not violate s. 3 of the Charter, despite government interference in the Boundaries Commission's mandate and significant disparities in district population. I argue that the Court's reasoning was flawed, and that it failed to protect disadvantaged minorities, evolve democracy or set appropriate standards to prevent gerrymandering. This becomes apparent when contrasting the Court's views of representation with a threefold theory of democratic elections (local representation, ideological expression and group decision-making). Discussing the role groups play in elections, this theory highlights the importance of 'one person-one vote', and how disparities between electoral districts lead to disparities in citizen voice and influence, damaging Canadian democracy. Adopting Mixed Member Proportional representation (MMP) would be a pragmatic solution to the Court's decision and the ongoing voter inequalities in Canada.

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)0.003
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.004
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.068
GPT teacher head0.426
Teacher spread0.358 · 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
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
Published2007
Admission routes1
Has abstractyes

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