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Record W2149172266 · doi:10.1017/s0008423906219991

Executive Styles in Canada: Cabinet Structures and Leadership Practices in Canadian Government

2006· article· en· W2149172266 on OpenAlexaffabout
Geoff Martin

Bibliographic record

VenueCanadian Journal of Political Science · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsMount Allison University
Fundersnot available
KeywordsCabinet (room)PoliticsPolitical scienceOpposition (politics)Public administrationGovernment (linguistics)House of CommonsLegislaturePower (physics)ManagementLawParliamentHistory

Abstract

fetched live from OpenAlex

Executive Styles in Canada: Cabinet Structures and Leadership Practices in Canadian Government, Luc Bernier, Keith Brownsey and Michael Howlett, eds., Toronto: University of Toronto Press, for The Institute of Public Administration of Canada, 2005, pp. xiii, 282. Executive Styles in Canada is a welcome addition to the literature on Canadian political leadership and provincial politics, essentially raising the question of the power of the premier, central agencies, and executive council in each of the Canadian provinces. To this end the editors have organized the book in 13 chapters. The book begins with a survey of the whole debate over “court government” raised by Donald Savoie, and the development model of Canadian cabinets advanced by Stefan Dupré and Christopher Dunn. The second chapter is given over to Savoie to make his case with respect to the federal government. His argument, by now familiar, is that by the 1990s the real power in the federal government is in the hands of the “prime minister and a small group of carefully selected courtiers” (17). Executive dominance of the legislature in the Westminster model has given way to even greater centralization. Power flows not from ministers, but from the prime minister. While Savoie does not address the seeming anomaly of the Paul Martin minority government of 2004–05, in which the House of Commons and even the opposition parties suddenly became relevant again, one gets the sense that he would argue that this is a temporary development rather than a more durable departure from the direction of the last 30 years.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.769
Threshold uncertainty score0.892

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.012
Science and technology studies0.0140.007
Scholarly communication0.0100.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.043
GPT teacher head0.282
Teacher spread0.239 · 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 designQualitative
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

Citations4
Published2006
Admission routes2
Has abstractyes

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