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Record W2064389533 · doi:10.5539/ies.v7n6p25

A Sociolinguistics Study on the Use of the Javanese Language in the Learning Process in Primary Schools in Surakarta, Central Java, Indonesia

2014· article· en· W2064389533 on OpenAlexvenueno aff
Kundharu Saddhono, Muhammad Rohmadi

Bibliographic record

VenueInternational Education Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Research and Methods
Canadian institutionsnot available
Fundersnot available
KeywordsIndonesianVocabularyLanguage acquisitionPsychologyFirst languageMathematics educationQualitative researchProcess (computing)LinguisticsPedagogyComputer scienceSociology

Abstract

fetched live from OpenAlex

This study aims at describing the use of language at primary schools grade 1, 2, and 3 in Surakarta. The study belongs to descriptive qualitative research. It emphasizes in a note which depict real situation to support data presentation. Content analysis is used as research methodology. It analyzes the research result of the observed speech event. The data are collected from three sources: informant, events, and documents. Results of the study demonstrate that the use of Javanese language is still dominant in the learning process at primary schools in Surakarta. Many factors affect the use of Javanese language as mother tongue in classroom teaching-learning process. They are (1) balancing the learning process, so that learners are able to better understand the material presented by the teacher (2) teacher’s habit to speak Javanese language, and (3) drawing student’s attention. The factors underlying this phenomenon are explained by teacher and student’s lack of Indonesian language vocabulary. In addition, there is an element unnoticed by teachers.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.187
GPT teacher head0.524
Teacher spread0.338 · 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

Citations92
Published2014
Admission routes1
Has abstractyes

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