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Record W1682137693 · doi:10.1017/cbo9780511560088.002

Federalism and Diversity in Canada

2000· book-chapter· en· W1682137693 on OpenAlexaboutno aff
Ronald L. Watts

Bibliographic record

VenueCambridge University Press eBooks · 2000
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsFederalismEthnic groupUnitary statePolitical scienceAutonomyDiversity (politics)PoliticsProtestantismNova scotiaPublic administrationGeographyEthnologySociologyLaw

Abstract

fetched live from OpenAlex

In a book aimed at exploring the role of federal political systems and autonomy arrangements in the management of ethnic differences and conflicts, this chapter focuses on the lessons, positive and negative, provided by the Canadian experience. While, in many respects, there are significant contrasts between Canada and other federations that must always be borne in mind, there are some features of the Canadian federation which make it particularly relevant to the examination of the interface between federalism and ethnic diversity. Unlike some other federations, such as the United States and Switzerland which were created by the aggregation of pre-existing states and cantons, the formation of Canada involved a substantial devolutionary process. A major part of its creation as a federation in 1867 was the splitting of the formerly unitary Province of Canada into two new provinces (Ontario, predominantly English-speaking and Protestant, and Quebec, predominantly Frenchspeaking and Roman Catholic), each autonomous and responsible for its own affairs in those areas where the two communities were sharply divided. To these provinces were added two smaller provinces (New Brunswick and Nova Scotia).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.895
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.171
Teacher spread0.153 · 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.

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

Citations22
Published2000
Admission routes1
Has abstractyes

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