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Record W4383555449 · doi:10.4324/9781003430001-11

The Canadian Paradox: Party System Stability in the Face of a Weakly Aligned Electorate

2023· book-chapter· en· W4383555449 on OpenAlexaboutno aff
Herman Bakvis

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsFace (sociological concept)Stability (learning theory)Political sciencePsychologyPolitical economyComputer scienceSociologySocial scienceMachine learning

Abstract

fetched live from OpenAlex

This chapter examines factors that might account for the paradox of system stability and weak alignment: the social underpinnings of the party system; institutional considerations such as the electoral system; and the behavior of parties and party leaders. The claim of volatility and lack of voter loyalty to parties has come under close scrutiny. The major parties lack both formal and informal connections to other organizations or social groupings which can be used to help mobilize support or aid in other ways. There tend to be two basic problems: overcoming internal considerations to select a leader capable of winning an election; and removing a leader whose usefulness has passed without too much public bloodletting. Party leadership appears to be a critical factor, but by its very nature it is fleeting and fickle. The Canadian paradox is a long standing phenomenon and may offer insight into the workings of those party systems now losing their structural underpinnings.

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)0.006
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 score0.070
Threshold uncertainty score0.511

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0140.010
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.047
GPT teacher head0.275
Teacher spread0.227 · 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

Citations16
Published2023
Admission routes1
Has abstractyes

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