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Record W3085946054

NABİ'NİN HAYRİYYE ADLI ESERİNDEKİ DEYİM VE ATASÖZLERİNİN TÜRKÇE DERS KİTAPLARINDA YER ALMA DURUMLARININ İNCELENMESİ

2017· article· tr· W3085946054 on OpenAlexaboutno aff
Yard. Doç. Dr. Rıza Oğraş

Bibliographic record

VenueAyrıntı Dergisi · 2017
Typearticle
Languagetr
FieldArts and Humanities
TopicTurkish Literature and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryVerbLinguisticsVocabularyOrder (exchange)Head (geology)PhilosophyHistoryNounQuarter (Canadian coin)PsychologyLiteratureArt
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT The idioms and proverbs among the cultural elements of Turkic are important language products. It has been used extensively in every stage of the development of the Turkic in order to make the expression effective. It is also possible to encounter these items frequently in the Divan literature which covers a phase of six syllables. In this literature, many currents and schools have been formed. Hikemi poetry from these; Thought-based, guiding and teaching poetry. It is seen that frequently used idioms and proverbs are used in order to get a deep sense in the works given in this movement. In this study, Nihbi's Hayriyye, the forerunner of Hikemi poetry that lived in the second half of the 17th century and the first quarter of the 18th century, was handled in terms of these language products. In order to determine the items mentioned in the study, Hayriyye-Yusuf Nâbi prepared by Iskender Pala was used as a basis and the screening was carried out taking into account the frequency and number of usage of the idioms and proverbs in the 1647 head. In the survey; 270 vocabulary 221 different idioms, 8 vocabulary 8 proverbs were detected. 71 of the idiomatic phrases are used in their original form today in couplets. Expressions in Hayriyye were classified as compound verb and noun group in terms of their structural features. It was seen that the expressions in the form of compound verb group in the direction of the obtained findings were used more than the phrases in the name group form. The phrases in Hayriyye 5-8. Class Turkish textbooks were presented and tabled.

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, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.446
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0090.004
Open science0.0040.001
Research integrity0.0020.003
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 head0.022
GPT teacher head0.242
Teacher spread0.219 · 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
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
Published2017
Admission routes1
Has abstractyes

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