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Record W4388570841 · doi:10.33701/jiwbp.v13i2.3178

PERMASALAHAN PELAYANAN PUBLIK DAN PERAN OMBUDSMAN PERWAKILAN DALAM PENDAMPINGAN APARATUR SIPIL NEGARA

2023· article· id· W4388570841 on OpenAlexaff
Andi Setyo Pambudi

Bibliographic record

VenueJurnal Ilmiah Wahana Bhakti Praja · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicPublic Administration in Developing Nations
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Pelayanan publik dalam praktiknya selalu terkait dengan lembaga penyelenggara layanan dan juga masyarakat sebagai penerima layanan. Lembaga yang menyelenggarakan pelayanan publik didukung salah satunya oleh adanya Aparatur Sipil Negara (ASN). Ombudsman RI sebagai Lembaga pengawas pelayanan publik sebagaimana amanah regulasi di Indonesia melakukan pendampingan terhadap aparatur sebagai bentuk upaya pencegahan maladministrasi. Meskipun demikian, lembaga ini di daerah (perwakilan) lebih dikenal dalam hal penyelesaian laporan/aduan masyarakat dalam pelayanan publik. Sementara itu, perencanaan pembangunan pelayanan publik harus memperhatikan kedua aspek ini (penyelesaian dan pencegahan) secara lebih berimbang berbasis permasalahan yang ada, kelembagaan lembaga pengawas dan wewenangnya serta tingkat popularitasnya didaerah. Hasil analisis dapat menunjukkan beberapa isu penting yang perlu ditangani berbasis prioritas, urgensi, lokasi dan pendapat publik. Peran dan popularitas Ombudsman, baik di pusat maupun daerah dalam pendampingan aparatur sipil negara dalam menjalankan pelayanan publik dan permasalahannya menjadi menarik diulas lebih dalam. Banyak praktik cerdas, peran maupun permasalahannya di lapangan dapat dijadikan masukan bagi pembangunan pelayanan publik sebagai bagian dukungan pada prioritas nasional dalam Rencana Pembangunan Jangka Menengah Nasional. Metode yang digunakan dalam analisis ini adalah mixed method melalui literature review, analisis big data dan FGD. Hasil analisis menunjukkan bahwa pada beberapa daerah Ombudsman sudah melaksanakan perannya dalam pendampingan namun belum merata sehingga diperlukan dukungan anggaran, regulasi, sarana dan prasarana serta sumber daya manusia yang memadai.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.149

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 studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0450.009

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 head0.048
GPT teacher head0.341
Teacher spread0.293 · 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 designQualitative
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

Citations5
Published2023
Admission routes1
Has abstractyes

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