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Federalism, federation and collective identities in Canada and Belgium: different routes, similar fragmentation

2001· book-chapter· en· W952888472 on OpenAlexaffabout
Dimitrios Karmis, Alain‐G. Gagnon

Bibliographic record

VenueCambridge University Press eBooks · 2001
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsFederalismFragmentation (computing)Political scienceRussian federationGeographyPublic administrationRegional scienceLawComputer science

Abstract

fetched live from OpenAlex

As exemplified in the simultaneous presence of rising trends towards atomization, economic, political and cultural integration, the proliferation of nationalist movements, and the multiplication of identity-based demands, the early twenty-first century is marked by tensions between universalism and particularism. These tensions tend to result in a growing polarization of political and theoretical positions, most often expressed through a debate on citizenship. Between the discourses of homogenizing universalism, exclusive nationalism, and postmodern hyperfragmentation or atomization, little space is left for a balance between unity and diversity. In this context, despite the recent collapse of federations in central and eastern European countries, most of those who believe in the suitability and feasibility of a balance between unity and diversity still consider federations – or some other type of federal system – as one of the most valuable options (see Kymlicka 1998b; Smith 1995a; Forsyth 1994, pp. 22–3; Norman 1994; Taylor 1993a; Gagnon 1993a, pp. 21–31). By way of a comparative study of the evolution of federalism, federation and collective identities in Canada and Belgium since the 1960s, this chapter seeks to demonstrate both the high importance and the major difficulties of reaching a federal balance between unity and diversity in multinational and polyethnic countries. A balance between unity and diversity – within a single multinational and polyethnic country – may be defined as the institutionalization of both the plurality and the asymmetry of allegiances in compatible ways.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.693

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.010
Science and technology studies0.0230.018
Scholarly communication0.0140.004
Open science0.0020.004
Research integrity0.0020.002
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 head0.018
GPT teacher head0.209
Teacher spread0.191 · 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 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

Citations14
Published2001
Admission routes2
Has abstractno

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