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Record W4409848592 · doi:10.29408/sosedu.v8i1.28036

INOVASI “LAPORRAMA” DALAM PELAYANAN PUBLIK DINAS KEPENDUDUKAN DAN PENCATATAN SIPIL KABUPATEN SINTANG

2024· article· en· W4409848592 on OpenAlexaff
Eka Apriyani, Akbar Wijaya, Sari Fipriyanti

Bibliographic record

VenueSOSIO EDUKASI Jurnal Studi Masyarakat dan Pendidikan · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

This research examines the implementation of LAPORRAMA, an innovative digital system introduced by the Disdukcapil of Sintang Regency, aimed at enhancing public satisfaction in civil registration services, particularly for birth and death certificates. The study investigates key issues such as accessibility, data accuracy, and transparency in service delivery within rural areas, where geographical challenges hinder access to essential documentation. Employing qualitative methods, including interviews with key stakeholders such as health officials and community leaders, the findings reveal that LAPORRAMA significantly streamlines administrative processes, reducing the time and effort required for obtaining vital records. Notably, the integration of this system facilitates immediate issuance of birth certificates at local health facilities, improving user experiences and mitigating the bureaucratic burdens associated with traditional manual processes. Additionally, LAPORRAMA addresses issues of corruption by ensuring transparency in administrative fees. Overall, the research highlights LAPORRAMA's critical role in enhancing the quality of public services and fostering trust in government institutions, thereby contributing positively to community well-being in Sintang Regency.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.304
Teacher spread0.275 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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