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Record W4386724758 · doi:10.55678/jia.v9i3.524

MODEL PEMBERDAYAAN MASYARAKAT TERHADAP PERENCANAAN PEMBANGUNAN DESA CARAWALI

2021· article· en· W4386724758 on OpenAlexaff
Hasmawati Hasmawati, Hariyanti Hamid, Kamaruddin Sellang

Bibliographic record

VenueJIA Jurnal Ilmiah Administrasi · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Administration in Developing Nations
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsEmpowermentLikert scaleData collectionPopulationCommunity developmentScale (ratio)SocioeconomicsSociologyGeographyPsychologyEconomic growthSocial scienceDemography

Abstract

fetched live from OpenAlex

The purpose of the study was to determine the community empowerment model for the implementation of development planning in carawali village, to find out whot factors were supporting and inhibiting community empowerment in the implementation of development planning in carawali villagr. The population of this study was 644 families, while the research sample was 87 families. Data collection techniques used in the study were observation, questionnaires and literature study, while the data analysis technique used was likert-scale data analysis. The collected data is then analyzed using a frequency table and using the SPSS application. The result of the research on community empowerment models for development planning in Carawali village, Wattang Pulu district, Sidenreng Rappang regency with an average value of 74,75% in the good category. The supporting factors for community empowerment on development planning in Carawali Village, Watang Pulu dictrict sidenreng rappang regency with a percentage of 57% while the inhibiting factors for community empowerment on development planning in Carawali Village, Wattang pulu district with a percentage of 49,4.

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 score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.002

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 head0.064
GPT teacher head0.363
Teacher spread0.299 · 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
Published2021
Admission routes1
Has abstractyes

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