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Record W4405113473 · doi:10.25306/skad.1446002

Şiddetin Topolojisi

2024· article· tr· W4405113473 on OpenAlexaboutno aff
Fatma Yavuz

Bibliographic record

VenueSosyal ve Kültürel Araştırmalar Dergisi (SKAD) · 2024
Typearticle
Languagetr
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsTheologyHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Güney Koreli yazar ve kültür kuramcısı Byung-Chul tarafından kaleme alınan Şiddetin Topolojisi, iki bölüm ve sekiz başlıktan oluşuyor. Kitabın ilk sayfaları yazarın okuyucuya tanıtıldığı bölüm olarak karşımıza çıkıyor ve aynı bölümde 2012 yılından beri Berlin Sanat Üniversitesi’nde ders veren yazarın günümüz toplumuna dair derinlikli çözümleme ve eleştirileriyle dikkat çektiğinden söz ediliyor. İlk basımı Mayıs 2016’da yapılan ve Eylül 2023 basımıyla Metis Yayınları’ndan çıkan kitap, giriş bölümünde “KAYBOLMAYAN şeyler vardır. Onlardan biri de şiddettir. Modernitenin şiddetten hazzetmediğini söyleyemeyiz.” diyerek çarpıcı bir başlangıç yapmakta. Şiddetin günümüzdeki görünümüne ve değişimselliğine vurgu yapılan aynı bölümde “…olumluluğun şiddeti vardır ve bu şiddet her türlü düşmandan ve iktidardan yoksun gerçekleşir.” diyerek ezber bozucu dilinin ilk sinyallerini vermektedir.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.084
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0050.003
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0840.018

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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