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Record W4385284361 · doi:10.1515/9781553392125

Canada: The State of the Federation, 2012

2015· book· en· W4385284361 on OpenAlexaboutno aff
Loleen Berdahl, André Juneau, Carolyn Hughes Tuohy

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2015
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsRussian federationState (computer science)Political scienceGeographyComputer scienceRegional scienceProgramming language

Abstract

fetched live from OpenAlex

Regional resource disparities and the tensions they generate are a perennial Canadian topic. This edition of Canada: The State of the Federation presents essays on regions, resources, and the resiliency of the Canadian federal system. Contributors consider questions such as: to what extent do Canada’s natural resource industries benefit the Canadian economy? Do Canada’s federal institutions hinder or promote the ability of the economy to respond to global economic shifts? Do current intergovernmental structures allow for constructive dialogue about national policy issues? In responding to these and related questions, many of the authors touch on energy issues. Others consider the importance of functional institutions in a federal or multilevel context as an essential requirement for the effective resolution of issues. Together, the volume raises questions about the relationship of state and society, the importance of identity, trust, and moral legitimacy for the operation of our federal institutions, and the extent to which federal institutions are reinforced or placed under stress by societal structures. The theme of this volume was triggered by Richard Simeon, the outstanding scholar of federalism who passed away in October 2013, and it is dedicated in his honour.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.904
Threshold uncertainty score0.697

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.008
Science and technology studies0.0120.003
Scholarly communication0.0090.003
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0670.015

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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

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