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Nationalism, Secessionism, and Autonomy

2021· book-chapter· en· W3199781402 on OpenAlexaboutno aff
André Lecours

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyPoliticsPolitical scienceNationalismPolitical economyAllianceNegotiationDevelopment economicsSociologyLawEconomics

Abstract

fetched live from OpenAlex

Abstract This chapter examines three additional cases: the Basque Country, Puerto Rico, and Québec. The objective behind these supplemental case studies is twofold. First, for the Basque Country, the goal is to understand why there has not been a strengthening of secessionism like in Catalonia. The chapter explains that Basque nationalism is exceptional for its history of political violence, which renders extremely difficult the type of alliance between nationalist forces that has occurred in Catalonia. Next, the chapter looks at Puerto Rico and Québec to assess how a focus on the nature of autonomy to explain the strength of secessionism travels beyond Western Europe. The case of Puerto Rico, where secessionism has always been marginal, helps to tease out the potential importance of perceptions on autonomy. Although Puerto Rican autonomy has not been adjusted, political debates over the constitutional future of the island, namely through multiple referendums on status, have likely fed perceptions that Puerto Ricans can change their autonomy, either through an enhancement of the current status or by becoming a state of the American federation. In Québec, the weakening of secessionism in the last decades has corresponded with a switch from constitutional reform to intergovernmental agreements as instruments for managing the position of the province within the federation. Constitutional change is difficult in Canada; consequently, Québec’s autonomy has been static constitutionally. As a result, when the focus for managing autonomy is placed on constitutional negotiations, secessionism in the province strengthens. When autonomy is managed through intergovernmental agreements, secessionism weakens.

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)0.003
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.765
Threshold uncertainty score0.472

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.012
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.292
Teacher spread0.265 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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