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Record W4402065276 · doi:10.58411/b1nsfj04

PENGUKURAN INDIKATOR PROGRAM PEMBANGUNAN BIDANG SOSIAL KOTA MALANG TAHUN 2022

2023· article· id· W4402065276 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePANGRIPTA · 2023
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

Pengukuran Indikator Pembangunan Bidang Sosial Kota Malang dilakukan untuk dapat mengukur capaian indikator kinerja program bidang sosial pada tahun 2021 dan tahun 2022 hingga triwulan dua, review target indikator pembangunan bidang sosial yang telah ditetapkan, menyajikan data-data indikator sosial, dan dapat memberikan rekomendasi kebijakan serta langkah-langkah yang perlu dilakukan oleh Pemerintah Kota Malang berdasarkan hasil kajian. Terdapat 23 (dua puluh tiga) program P-RPJMD dan 54 (lima puluh empat) indikator pada bidang sosial yang sesuai dengan perangkat daerah terkait. Pengukuran indikator program pembangunan bidang sosial ini memiliki teknik analisis pengukuran capaian indikator bidang sosial, pengukuran efektivitas capaian target, pengelompokan tingkat efektivitas capaian target, dan identifikasi faktor determinan pelaksanaan program. Hasil dari analisis tersebut menunjukkan bahwa sejumlah 80% indikator telah memiliki tingkat efektivitas yang sangat tinggi di tahun 2021. Efektivitas tersebut meningkat dari tahun sebelumnya dengan selisih 23%. Akan tetapi masih terdapat 3 (tiga) indikator yang memiliki tingkat efektivitas sangat rendah dan 2 (dua) indikator memiliki tingkat efektivitas rendah.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.020

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 head0.032
GPT teacher head0.240
Teacher spread0.208 · 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