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Record W3184170762 · doi:10.46730/jiana.v19i1.7962

PARTISIPASI PASANGAN USIA SUBUR DALAM PELAKSANAAN PROGRAM KAMPUNG KELUARGA BERENCANA DI DESA PULAU KERASIAN KABUPATEN KOTABARU

2021· article· id· W3184170762 on OpenAlexaff
Irna Oktavianita, Taufik Arbain

Bibliographic record

VenueJIANA ( Jurnal Ilmu Administrasi Negara ) · 2021
Typearticle
Languageid
FieldSocial Sciences
TopicLocal Governance and Development
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical scienceGynecologyHumanitiesMedicineArt

Abstract

fetched live from OpenAlex

Tujuan penelitian ini adalah untuk mengetahui penyebab rendahnya partisipasi partisipasi pasangan usia subur dalam pelaksanaan program KB Kampung di Desa Pulau Kokasian Kecamatan Laut Kepulauan Kabupaten Kotabaru. Kemudian diuraikan dan dianalisis dari determinan keberhasilan implementasi implementasi kebijakan publik menurut Edward III yaitu komunikasi, sumber daya, disposisi, struktur birokrasi untuk mencapai tujuan penelitian peneliti menggunakan metode kuantitatif, dengan analisis deskriptif. Variabel yang digunakan adalah komunikasi, sumber daya, disposisi, dan struktur birokrasi. Hasil penelitian dari 37 pertanyaan dianalisis menggunakan analisis parsial yang ditabulasi dan frekuensi menghasilkan analisis pengaruh komunikasi sebesar 33%, sumber daya sebesar 47%, disposisi sebesar 36%, struktur birokrasi sebesar 32%. Kesimpulannya, penyebab paling dominan rendahnya partisipasi pasangan usia subur dalam pelaksanaan program Desa Keluarga Berencana adalah Sumberdaya karena memiliki pengaruh sebesar 47% terhadap rendahnya partisipasi pasangan usia subur dalam pelaksanaan KB Desa. Program di Desa Pulau Kerasian, Kecamatan Pulau Laut Kepulauan, Kabupaten Kotabaru.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.318
Teacher spread0.287 · 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
Published2021
Admission routes1
Has abstractyes

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