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Record W2734257280 · doi:10.1093/publius/pjx043

Introducing a Societal Culture Index to Compare Minority Nations

2017· article· en· W2734257280 on OpenAlexaffabout
Félix Mathieu, Dave Guénette

Bibliographic record

VenuePublius The Journal of Federalism · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsUniversité LavalUniversité du Québec à Montréal
Fundersnot available
KeywordsMultinational corporationPolitical scienceIndex (typography)PoliticsSovereigntyCorporate governanceState (computer science)NormativeDemocracyMinority rightsEmpirical researchPolitical culturePolitical economyPublic administrationSociologyEconomic growthDevelopment economicsLawEconomics

Abstract

fetched live from OpenAlex

Unlike sovereign nations, minority nations cannot fully empower their societal cultures exclusively with their own autonomous institutions, because they are evolving within a larger political state and a more comprehensive legal order. In this article, we compare Catalonia, Quebec, and South Tyrol with regard to their legal capacity to develop their societal culture by their own autonomous institutions. In doing so, we identify six legally oriented pillars that are central for a minority nation to sustain its societal culture, on the one hand, and that are fundamental for a multinational (quasi)federation to feed a healthy democratic and hospitable environment for all, on the other hand. Those pillars form the building blocks of the Societal Culture Index, which allows measuring and comparing minority nations by combining normative studies and empirical research. Hence, we argue that governance in (quasi)federal system will be improved to the extent that minority nations score as high as possible on the Index.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
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 head0.033
GPT teacher head0.341
Teacher spread0.308 · 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

Citations15
Published2017
Admission routes2
Has abstractyes

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Same venuePublius The Journal of FederalismSame topicPolitical Systems and GovernanceFrench-language works237,207