MétaCan
Menu
Back to cohort
Record W4384081459 · doi:10.21002/jke.2022.10

Infrastruktur Jalan dan Kriminalitas di Pedesaan Indonesia

2022· article· id· W4384081459 on OpenAlex
Winda Vidyaras

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

VenueJurnal Kebijakan Ekonomi · 2022
Typearticle
Languageid
FieldSocial Sciences
TopicLegal Studies and Policies
Canadian institutionsEncana (Canada)
FundersCurtin University of Technology
KeywordsPolitical scienceGeographyHumanitiesArt

Abstract

fetched live from OpenAlex

Penelitian ini melihat bagaimana infrastruktur jalan mempengaruhi kriminalitas di pedesaan Indonesia. Sejak dikeluarkannya Undang-Undang No. 6 Tahun 2014 tentang Desa, terjadi pembangunan masif infrastruktur jalan untuk mengembangkan perekonomian desa. Namun, pembangunan jalan tersebut menimbulkan adanya eksternalitas negatif, yaitu kriminalitas. Dengan model regresi logistik, penelitian ini menganalisis data Potensi Desa tahun 2006-2018 di seluruh Indonesia. Hasil menunjukkan bahwa pembangunan infrastruktur jalan di pedesaan umumnya beriringan dengan peningkatan peluang kriminalitas sekitar 1,3-1,5 kali lebih tinggi. Setelah pembangunan masif, terindikasi peningkatan ekonomi yang berdampak pada turunnya kriminalitas di desa-desa terpencil. Temuan ini mendukung literatur infastruktur jalan dan aksesibilitas dapat memberikan peluang terjadinya kriminalitas.

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), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.024
GPT teacher head0.287
Teacher spread0.263 · 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