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Record W2896765958 · doi:10.15273/jue.v8i2.8686

“Of Course, I am a Human Being, Too”: Nationalism and Contact in the Republic of Turkey and State of Israel

2018· article· en· W2896765958 on OpenAlexvenueno aff
C. Phifer Nicholson

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPrejudice (legal term)NationalismSociologyState (computer science)HumanismGender studiesEthnic groupNarrativeEmbodied cognitionNegotiationEthnographyPolitical scienceSocial psychologyPsychologySocial scienceLawEpistemologyAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

This article analyzes the secular and religious nationalisms in the Republic of Turkey and State of Israel as experienced by ethnic and religious minorities in both locales. This ethnographic work focuses on the embodied experiences of individuals in their religious, political, and social entirety, seeking to delve into their lives as an oft-neglected or feared group, and explore their contact (or lack thereof) with members of the majority culture. Semi-structured interviews revealed historical and present-day structures created and maintained through avenues such as media, education, literature, language, and politics that seek to define and separate groups that do not fit the prevailing nationalistic narratives. This is exacerbated by negative contact that is generally oriented around political disagreement and conflict. However, in some cases, positive intergroup contact served to facilitate fundamental changes. Therefore, despite its limitations, contact has the potential to not only reduce prejudice, but also inspire lives of political and humanistic engagement that can undermine the “single stories” stigmatization propagates.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.098
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.036
GPT teacher head0.371
Teacher spread0.335 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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