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EKSPLORASI KEARIFAN LOKAL MELALUI TEKS NARATIF: STUDI RITUAL TEKES MASYARAKAT SUKU LAMASI DALAM PEMBELAJARAN BAHASA INDONESIA

2025· article· W7134264639 on OpenAlexaff
Katharina Nay, Florianus Aloysius Nay, Rudobertus Talan

Bibliographic record

VenueJurnal Pendidikan Dasar Borneo (Judikdas Borneo) · 2025
Typearticle
Language
FieldSocial Sciences
TopicMulticultural Education and Local Wisdom
Canadian institutionsThe Audio Recording Academy
Fundersnot available
KeywordsIndonesianNarrativeLiteracyNarrative inquirySymbol (formal)Qualitative research

Abstract

fetched live from OpenAlex

This study aims to explore the local wisdom values contained in the Tekes traditional ritual of the Lamasi people in Insana District, North Central Timor Regency, and to explore its potential as a narrative text in Indonesian language learning. The research approach used is descriptive qualitative with narrative ethnography. Data were collected through in-depth interviews, participatory observation, documentation, and literature studies. The results show that the Tekes ritual is a form of respect for ancestors carried out through cultural symbols such as hauteas, nyiru, traditional cloth, betel nut, and sacrificial animals. Each symbol contains values such as religiosity, solidarity, respect for ancestors, and spiritual strength. The narrative structure of the Tekes procession includes elements of orientation, complication, resolution, and coda, which are in accordance with the basic competencies of narrative texts in the Indonesian language curriculum. The integration of Tekes as teaching material can strengthen student literacy while building cultural awareness and local identity. This study recommends the need for the development of local wisdom-based learning and cultural preservation by communities and educational institutions collaboratively.

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)0.004
metaresearch head score (Gemma)0.002
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), Science and technology studies, 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: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.005
Science and technology studies0.0060.004
Scholarly communication0.0030.003
Open science0.0040.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.002

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 head0.019
GPT teacher head0.340
Teacher spread0.321 · 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
Published2025
Admission routes1
Has abstractyes

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