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Record W2183422742 · doi:10.22215/cjers.v4i2.2456

‘Making the Margins of Europe’: Marginalization, Europeanization and Islam in the contest for Public Space.

2008· article· en· W2183422742 on OpenAlexvenueno aff
Jason Young

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean unionIslamPoliticsPolitical sciencePolitical economyCONTESTNation stateGender studiesSociologyLawGeography

Abstract

fetched live from OpenAlex

This article intervenes into the debate around European identity, political Islam, and Turkey’s potential accession to the European Union through treating Samuel Huntington’s “Clash of Civilizations” as a bordering discourse. The article argues that the ‘clash thesis’ highlights uncertainty around cultural change in Europe as well as a tension within European Integration itself between the Nation as State and the Nation as political and cultural identity. Discourses which position specific groups as being unEuropean, or less European can be linked to the shifting meaning of Europe in light of political and economic integration and its affects on the Nation as titular owner of the State. The article argues that the debate around the compatibility of Islam and Europe and therefore, also the debate around Turkey’s accession to the European Union must be situated within the context of boundary formations driven by im/migration to Europe and within Europe and the rise in public visibility and assertiveness by second and third generation Islamic communities, thereby moving the debate beyond the Self /Other dichotomy upon which the ‘clash thesis’ functions by understanding the boundaries of Europe as negotiable and culturally situated within a publicly mediated discourse about ‘Europe’.
 
 Full text available at: https://doi.org/10.22215/rera.v4i2.200

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.139
GPT teacher head0.319
Teacher spread0.180 · 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 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

Citations1
Published2008
Admission routes1
Has abstractyes

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