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Record W4412815969 · doi:10.12928/jampe.v4i2.13011

How is the Social Community of Malang City? Index Study and Performance Analysis

2025· article· en· W4412815969 on OpenAlexaff
Lustina Fajar Prastiwi, Trianingsih Eni Lestari, Risa Saadiyah, Jayson Troy Ferro Bajar, Hopkins Henry Kawaye

Bibliographic record

VenueJAMPE (Journal of Asset Management and Public Economy) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Administration in Developing Nations
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsIndex (typography)SociologyPsychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The purpose of this study was to determine the Community Development Index (IPMas) of Malang City in 2024 using Importance Performance Analysis (IPA). IPMas can be seen from the Tolerance Index, Mutual Cooperation Index, and Sense of Security Index. The result is that overall IPMas Malang City got a score of 87.56%. This value tends to remain the same but can increase if various programs are implemented properly related to the cooperation index, tolerance index, and sense of security index. Malang City has realized a friendly city by paying attention to aspects of tolerance, mutual cooperation, and adequate sense of security. The contribution of this paper is to explain the performance of the Malang city government in the social community sector. The success of the regional government's performance can be measured not only by economic growth, but also by the influence of government performance on the community development index.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.328
Teacher spread0.287 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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