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Record W4385319981 · doi:10.61076/jpp.v4i2.3065

PERENCANAAN PEMBANGUNAN PARTISIPATIF GUNA MEWUJUDKAN ASPIRASI MASYARAKAT DI BADAN PERENCANAAN PEMBANGUNAN DAERAH KABUPATEN MUSI BANYUASIN

2022· article· en· W4385319981 on OpenAlexaff
Ridwan Ridwan, Juwandi Panab

Bibliographic record

VenueJurnal Pallangga Praja (JPP) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Administration in Developing Nations
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsGovernment (linguistics)Community participationState (computer science)Community developmentSpace (punctuation)Local governmentSociologyQualitative researchDescriptive researchPublic administrationPublic relationsEconomic growthPolitical scienceSocioeconomicsSocial scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

development that prospers the community is development that is universal in all sectors of the social life ofsociety. To achieve development goals, massive and intensive cooperation and collaboration between the government and the community is needed. Creative and intensive collaboration carried out in Musi Banyuasin Regency by conducting development Planning Consultations or Musrembang. Musrembang is a policy-makingprocess involving active community participation in channeling their aspirations. This research was conductedto identify community participation in policy making and the inhibiting and supporting factors of communityparticipation. This research was conducted using a qualitative method with a descriptive approach that describes the state of community participation in development. This study uses data analysis using participatorydevelopment planning theory by McGee which includes the following dimensions: actors (People), Knowledge(Knowledge) and spaces (space). Based on the results of the research, to build community participation in development the Government has assigned sub-districts and villages to immediately prepare the implementationof the annual musrenbang and immediately socialize it to the community. The program has been running well,but there are obstacles in the form of funding in the process of organizing activities.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0320.005

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 head0.040
GPT teacher head0.326
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; 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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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