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Record W2116695861 · doi:10.17572/mj2014.1.3755

REVISITING NATIONAL SECURITY DISCOURSE IN TURKEY WITH A VIEW TO PACIFICATION: FROM MILITARY POWER TO POLICE POWER ONTO ORCHESTRATION OF LABOUR POWER

2014· article· en· W2116695861 on OpenAlexaff
Gülden Özcan

Bibliographic record

VenueMoment Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsCarleton University
Fundersnot available
KeywordsHegemonyNational securitySolidarityNeoliberalism (international relations)Power (physics)SociologyPoliticsPolitical economySecuritizationPolitical scienceLawEconomics

Abstract

fetched live from OpenAlex

In this article, I try to analyse the neoliberal re-structuration in Turkey with a view to fabrication of official national security discourse and its adaption as common sense among productive classes. Acknowledging pacification as a counter-hegemonic approach to securitization, I offer an alternative framework to study the role of national security in Turkish politics that goes beyond rather traditionalized civil-military dichotomy. I argue that national security is a technique aiming at pacification with both imperial and local targets and that it should be understood with recourse to the neoliberalism-security-pacification axis. The article composes of three sections. First, I explore the history of the term pacification. Second, I look at the discursive continuities on national security between the military regime and the civilian AKP governments. Third, I reflect on the alternative forms of solidarity emerged during the Gezi Resistance that open the possibility of creating a counter-hegemonic common sense.

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)0.003
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.015
Scholarly communication0.0080.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.316
Teacher spread0.299 · 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 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

Citations2
Published2014
Admission routes1
Has abstractyes

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