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Record W4312782233 · doi:10.36341/jdp.v5i1.2247

Deliberasi dalam Perencanaan Pembangunan Infrastuktur Nagari Kunangan Parit Rantang, Kecamatan Kamang Baru pada Masa Covid-19

2022· article· id· W4312782233 on OpenAlexaff
Lingga Elissa

Bibliographic record

VenueJDP (Jurnal Dinamika Pemerintahan) · 2022
Typearticle
Languageid
FieldSocial Sciences
TopicCOVID-19 Prevention and Impact
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical sciencePhysics

Abstract

fetched live from OpenAlex

Artikel ini membahas proses deliberatif untuk membuat hasil berupa kesepakatan yang dijadikan kebijakan atau dasar rencana pengelolaan suatu entitas pemerintahan. Fokus penelitian meliputi empat hal, pertama, Proses Deliberasi Dalam Perencanaan Pembangunan Nagari Kunangan Parit Rantang, kedua, Kelompok Yang Dilibatkan Dalam Musrenbang Nagari Kunangan Parit Rantang, ketiga, Indikator Keberhasilan Pelaksanaan Musrenbang, dan keempat, Perbedaan Pelaksanaan Musrenbang Di Nagari Kunangan Parit Rantang Pada Masa Sebelum Pandemi dan Saat Pandemi. Tujuan dari penelitian ini adalah untuk mengetahui bagaimana partisipasi masyarakat dalam musyawarah pembangunan infrastruktur Nagari Kunangan Parit Rantang, Kecamatan Kamang Baru pada masa pandemi covid-19. Pandemic covid-19 mempengaruhi jumlah skala pembangunan infrastruktur di Nagari Kunangan Parit Rantang, Kecamatan Kamang Baru. Metode penelitian ini menggunakan metodeIkualitatif yang dikembangkan melalui sebuah fenomena dan didukung oleh pendapat para ahli dengan menggunakan data yang telah diperoleh sebelumnya. Kesimpulan yang didapat dalam penelitian ini ialah, pemahaman demokrasi deliberatif dalam pembangunan infrastruktur yang ada di Nagari Kunangan Parit Rantang Kecamatan Kamang Baru.

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)0.001
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0070.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0430.001

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 head0.036
GPT teacher head0.340
Teacher spread0.304 · 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 teacher head, not a consensus.

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
Published2022
Admission routes1
Has abstractyes

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