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Record W4411759238 · doi:10.53299/bajpm.v5i2.2057

Pelatihan Manajemen dan Penanganan Kasus Perempuan dan Anak di Kota Bima Nusa Tenggara Barat

2025· article· id· W4411759238 on OpenAlexaff
Nurnazmi Nurnazmi, Syahru Ramadan, Tasrif Tasrif, Syaifullah Syaifullah, Ida Waluyati, Syahruddin Syahruddin

Bibliographic record

VenueBima Abdi Jurnal Pengabdian Masyarakat · 2025
Typearticle
Languageid
FieldSocial Sciences
TopicGender and Women's Rights
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Tujuan pelatihan manajemen dan penanganan kasus perempuan dan anak antara lain: (a) Peserta diharapkan mampu mengenali dan memahami dalam menangani masalah perempuan dan anak yang terjadi di tengah masyarakat. (b) Peserta dapat mengsimulasi dalam menangani kasus perempuan dan anak melalui sketsa gambar dan deskriptif, (c) Peserta dapat mengimplementasikan alur manajemen kasus perempuan dan anak, (d) Peserta dapat menganalisis policy output dalam penanganan kasus perempuan dan anak, (e) Peserta mampu mendeskripsikan alur manajemen kasus dan policy output dalam penanganan kasus perempuan dan anak di Kota Bima Nusa Tenggara Barat. Metode pelatihan manajemen dan penanganan kasus untuk perlindungan perempuan dan anak antara lain: perjalinan relasi (engagement), penilaian (assessment), rencana (planning), intervensi (intervetion), pemantauan (monitoring), evaluasi (evaluation), terminasi (termination), dan tindak lanjut (follow-up). Peserta 35 orang dibagi ke dalam 5 kelompok dan menangani kasus perempuan dan anak yang berbeda-beda seperti kakerasan terhadap perempuan (KTP), kekerasan terhadap anak (KTA), Tindakan Pidana Perdagangan Orang (TPPO), Anak Berhadapan dengan Hukum (ABH), dan Pernikahan Usia Anak. Peserta dapat mengilustrasikan dan mendekripsikan kasus perempuan dan anak di masyarakan menggunakan simulasi gambar. Peserta mengilustrasikan dan mempresentasikan manajemen dan penanganan kasus perempuan dan anak.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0050.002
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.282
Teacher spread0.262 · 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 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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