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Record W3127269972 · doi:10.22055/rals.2020.16296

Linguistic Analysis and Contents of the «Book for Reading» By Kasim Bikkulov (Early Twentieth Century)

2020· article· en· W3127269972 on OpenAlexaboutno aff
Nuriyeva Liliya Failevna, Sayfulina Flera Sagitovna, Mingazova Liailia Ihsanovna, Kayumova Gelyusya Faridovna

Bibliographic record

VenueJournal of research in applied linguistic studies/Journal of research in applied linguistics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsTatarReading (process)LiteratureQuarter (Canadian coin)LinguisticsHistoryArtSociologyArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

The article is devoted to the Linguistic analysis of Books for reading by the early 20th-century enlightener writer Kasim Bikkulov, known as a writer, educator, the religious figure from the standpoint of identifying the structural and linguistic features of collections and the contents of the texts included in them. The purpose of this article is the study of Books for Reading by Kasim Bikkulov, the analysis of collection structure, the thematic trends of literary works, and texts of a scientific and journalistic nature included in collections. The paper used analytical, hermeneutics, comparative, and cultural-historical research methods. The analysis makes it possible to conclude that the Books for Reading of the studied author constitute a special place in the activities of the teacher-educator and are a definite contribution to children's literature, and also serve as an example of textbooks widely used in the teaching of Tatar literature at primary school during the first quarter of the XX-th century.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0030.003
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.230
GPT teacher head0.497
Teacher spread0.268 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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