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Record W7132239795

Mehmed Zihni Efendi'nin Arap lügatçiliğindeki yeri

2018· dissertation· tr· W7132239795 on OpenAlexaboutno aff
Elif Gül Gökhan

Bibliographic record

VenueMarmara University Open Access System · 2018
Typedissertation
Languagetr
FieldPsychology
TopicFamilies in Therapy and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)TurkishGovernment (linguistics)Bin
DOInot available

Abstract

fetched live from OpenAlex

“Mehmed Zihni Efendi’nin Arap Lügatçiliğindeki Yeri” adlı tez çalışmamızda amacımız Osmanlı Devleti’nin son dönemlerinde yetişmiş büyük İslam alimlerinden Mehmed Zihni Efendi’nin sözlük kullanımına verdiği önemi göstererek sözlüklerin edebi ve ilmi açıdan işlevselliğini vurgulamak ve telif ettiği bir sözlüğü bulunmadığı halde kendisinin sözlük alanına katkılarını ortaya koymaktır. Çalışmamız iki bölüm ve ekten oluşmaktadır. İlk bölümde konuya temel olarak Arap dilinde sözlük çalışmaları ve sözlük yazım ekolleri, Osmanlı döneminde yapılan Arapça-Türkçe sözlük çalışmaları hakkında bilgi verdik. İkinci bölümde ise Zihni Efendi’nin Arap dili grameri ve edebiyatına dair Müntehab, Muktedab ve el-Kavlü’l-ceyyid adlı eserlerini inceleyerek hangi sözlüklerden, ne sıklıkla ve hangi sebeplerle faydalandığını tespit edip sözlüklerden istifade yöntemini ortaya koymaya çalıştık. Zihni Efendi’nin Türkçe açıklamalarda bulunduğu Arapça kelimeleri derleyerek meydana getirdiğimiz sözlük çalışmasını tertip, dil, anlam ve dil bilgisi yönünden inceleyerek tespitlerimizi dile getirdik. Zihni Efendi’nin özgünlüğünü görebilmek adına belli başlı kelime açıklamalarını Ahterî, Vankulu Lügati ve Kâmûs Tercümesi ile karşılaştırdık. Zihni Efendi adına oluşturduğumuz yedi bin küsür kelimelik sözlük çalışmasını ise ekte sunduk.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.240
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0140.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.005

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 head0.093
GPT teacher head0.418
Teacher spread0.324 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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