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IMPLEMENTASI PERMAINAN TRADISONAL SENAPAN BAMBU UNTUK KEMAMPUAN SOSIAL ANAK USIA DINI

2022· article· id· W4287312723 on OpenAlexaff
Silfia Ningsih, Nina Khayatul Virdyna

Bibliographic record

VenueJP2KG AUD (Jurnal Pendidikan Pengasuhan Kesehatan dan Gizi Anak Usia Dini) · 2022
Typearticle
Languageid
FieldSocial Sciences
TopicChild Development and Education
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan Mengetahui bagaimana Implemetasi permaianan tradisional senapan bambu untuk kemampuan sosial anak usia dini. Berdasarkan hal tersebut, maka ada tiga permasalahan yang menjadi fokus utama dalam penelitian ini, yaitu: bagaimana Implemetasi permaianan tradisional senapan bambu untuk kemampuan sosial anak usia dini. Kedua, manfaat apa saja dari Implemetasi permaianan tradisional senapan bambu untuk kemampuan sosial anak usia dini. Ketiga, faktor pendukung dan penghambat dalam Implemetasi permaianan tradisional senapan bambu. Penelitian ini menggunakan pendekatan Kualitatif dengan jenis deskriptif. Informannya adalah kepala sekolah, guru dan siswa. Hasil penelitian ini menunujukkan bahwa implementasi permainan tradisional senapan bambu sangat sederhana. Kedua, Media pembelajaran yang efektif, kreativitas guru, antusias peserta didik dan tekhnik mengajar yang menarik, sedangkan faktor penghambat dari implementasi permainan senapan bambu yaitu, anak yang tidak patuh dan tidak mau mengikuti aturan,sifat anak yang masih agresif, usia anak yang masih terbilang dini dan Pemalu.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0480.006

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 head0.033
GPT teacher head0.309
Teacher spread0.276 · 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 designObservational
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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