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Record W2332789474 · doi:10.1017/s0008423911000485

Combining the Hazards of Ministerial Appointment AND Ministerial Exit in the Canadian Federal Cabinet

2011· article· en· W2332789474 on OpenAlexaffabout
Matthew Kerby

Bibliographic record

VenueCanadian Journal of Political Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCabinet (room)Political sciencePoliticsHumanitiesLawGeographyPhilosophy

Abstract

fetched live from OpenAlex

Abstract. The Canadian federal cabinet stands out among Westminster parliamentary democracies because of the large number of first-time ministers who are appointed to cabinet without any previous parliamentary or political experience. Several explanations have been put forward to account for this peculiarity but no attempt has been made to examine how Canadian prime ministers overcome the information deficit associated with appointing ministers with no experience. How can prime ministers be confident that they are making the right choice? This paper explores the subject by estimating the survival functions of ministerial turnover for potential, but not yet appointed, cabinet ministers were they to survive to a defined political benchmark; these survival rates are included in a logit model of Canadian ministerial appointment following four general elections (1957, 1979, 1984 and 2006) in which the prime minister was tasked with appointing a cabinet with ministerial neophytes. Résumé. Le Conseil des ministres fédéral du Canada se démarque dans l'ensemble des démocraties parlementaires britanniques en raison du grand nombre de ministres novices qui sont nommés au Conseil alors qu'ils ne possèdent aucune expérience parlementaire ou politique antérieure. Plusieurs explications de cette anomalie ont été proposées, mais aucune démarche d'analyse ne s'est encore penchée sur la manière dont les premiers ministres du Canada arrivent à surmonter le manque d'information associé à la nomination de ministres sans expérience. Comment les premiers ministres peuvent-ils être certains d'avoir fait le bon choix? Cette étude scrute le sujet en évaluant le coefficient de survie, en cas de remaniement ministériel, pour les ministres du Conseil potentiels, mais pas encore mandatés, advenant que ces derniers survivent à certains jalons politiques précis. Ces taux de survie font partie intégrante d'un modèle de répartition des nominations ministérielles qui sont survenues à la suite de quatre élections générales (1957, 1979, 1984 et 2006) où le premier ministre a dû constituer un Conseil des ministres composé de néophytes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.087
GPT teacher head0.335
Teacher spread0.248 · 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 teacher head, 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

Citations16
Published2011
Admission routes2
Has abstractyes

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