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Record W7161774268 · doi:10.82308/17664

Electoral systems, veto players, and substantive representation: when majoritarian electoral systems strengthen the citizen-policy nexus

2015· dissertation· en· W7161774268 on OpenAlexaboutno aff
Benjamin Ferland

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
Fundersnot available
KeywordsVetoNexus (standard)Proportional representationRepresentation (politics)PoliticsGovernment (linguistics)IncentiveDemocracy

Abstract

fetched live from OpenAlex

The dissertation addresses a question that is at the very heart of democratic representation and the functioning of democracy: what kind of electoral system fosters the correspondence between what the public wants and what the public gets? In light of recurring debates about reform of the electoral system in Canada and abroad, this question remains crucial to address. In the first part of the dissertation, this question is examined thoroughly building on two influential literatures on political representation. On the one hand, we examine whether governments' ideological positions correspond to citizens' positions over the course of government mandates under majoritarian and proportional representation electoral systems. On the other hand, we examine the adjustments that governments make to their welfare spending over time in response to citizens' preferences under majoritarian and PR electoral systems. In both cases, we show that the citizen-policy nexus is strengthened under majoritarian electoral systems rather than under proportional representation systems. We explain these results based on a veto player approach that accounts for the capacity of a government to change its policies and the incentives that governments have to adopt policies that match the preferences of citizens. In the second part of the dissertation, we examine the impact of electoral systems on citizens' satisfaction with the way democracy works. We are interested first in the impact of correspondence between government policies and citizens' preferences on citizens' assessment of the functioning of the political system. We show that citizens are responsive to the policies adopted by governments and that this influences their satisfaction with the way democracy works. In the last chapter of the dissertation, we address an unresolved question related to the impact of electoral representation on citizens' democratic satisfaction. While there is a consensus in the literature that PR electoral systems foster an accurate translation of votes into seats it remains unclear whether citizens' satisfaction is enhanced by such "accurate" electoral representation. Building on new insights from the political participation literature, we offer an answer to this conundrum by showing that citizens' satisfaction with the way democracy works is bred by rationality rather than virtue. Overall, the dissertation contributes to a better understanding of the institutional arrangements that maximize the citizen-policy nexus by offering evidence about the superiority of majoritarian electoral systems over proportional representation electoral systems in fostering this substantive component of the representational process. While scholars have generally accepted the view that majoritarian systems enhance accountability and PR systems favour political representation we show throughout the dissertation that majoritarian systems could actually score high on both dimensions.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.072
GPT teacher head0.383
Teacher spread0.311 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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