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Record W4312243367 · doi:10.1080/09637494.2022.2129242

State-religion relations in Southern and Southeastern Europe: moderate secularism with majoritarian undertones

2022· article· en· W4312243367 on OpenAlexaff
Tina Magazzini, Anna Triandafyllidou, Liliya Yakova

Bibliographic record

VenueReligion State & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSecularismState (computer science)Political scienceNationalismTypologyPolitical economySociologyDevelopment economicsLawPoliticsAnthropology

Abstract

fetched live from OpenAlex

This contribution studies comparatively three Southern European countries (Italy, Spain, and Greece) and three Southeastern European countries (Albania, Bosnia and Herzegovina, and Bulgaria). Looking beyond historical path-dependencies, we investigate recent developments in terms of state-religion relations. Starting with a thick description of the historical legacies and post-1989 developments, we focus on issues of the last decade, such as the rise of populism and nationalism, the path to EU accession for Bosnia and Albania, the economic and Eurozone crisis of the 2010s, and the refugee emergency of 2015. Our aim is to assess how these have shaped state-religion relations and to categorise the six countries within the typology proposed in the introductory contribution to this collection. Our findings suggest that moderate secularism and liberal neutralism prevail in all six countries. There are, however, important variations in terms of the relevance of majoritarian nationalism in some of them, as the state defines the prevailing religion and has strong historical and institutional ties with that religion. The contribution elaborates on these specificities and concludes with some questions on the importance of the notion of dominant vs qualifying norms and on the role of current challenges in shaping further state-religion relations.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.266
Teacher spread0.253 · 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 designQualitative
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

Citations6
Published2022
Admission routes1
Has abstractyes

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