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Record W3183445109

In Defense of Majoritarianism

2017· article· en· W3183445109 on OpenAlexaboutno aff
Stanley L. Winer

Bibliographic record

VenueRePEc: Research Papers in Economics · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHouse of CommonsReferendumPolitical scienceContext (archaeology)Proportional representationPresidencyHonorElectoral reformElectoral collegeVictoryState (computer science)Representation (politics)LawDemocracyPublic administrationLaw and economicsPoliticsSociologyVotingParliamentHistory
DOInot available

Abstract

fetched live from OpenAlex

Few people have bothered to defend the Majoritarian, winner take all character of the current Canadian electoral system. This parliamentary system has been in existence in the same form since the founding of the modern state in 1867. In these remarks, I offer a defense of Majoritarianism in the Canadian context when the alternative is some form of Proportional Representation. These remarks were prepared as an opening statement in a debate on electoral reform at a Faculty of Public Affairs 75th Anniversary conference at Carleton University, March 3, 2017. \n \nThe debate arose because of the Prime Minister's announced intention to replace the current system with some other during the election campaign that led to his victory in 2015. The debate occurred a few months after the release of a lengthy report on electoral reform by a special allparty committee of the House of Commons. A few weeks before the debate, the Prime Minister announced (independently of the debate, of course) that his government would no longer pursue electoral reform, perhaps because it looked like he would not be able to avoid a referendum, a process which is hard to control. In any event, and especially in the light of recent attempts to change the system both at the federal level and in some provinces, I think it is important for people to understand that the existing electoral system is a sensible one that likely will continue to serve us well.

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)0.010
metaresearch head score (Gemma)0.017
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 score0.270
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0110.063
Scholarly communication0.0120.004
Open science0.0020.006
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0080.001

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 head0.042
GPT teacher head0.364
Teacher spread0.322 · 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
Published2017
Admission routes1
Has abstractyes

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