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ZONA PERI-URBAN SEMARANG METROPOLITAN: PERKEMBANGAN DAN TIPOLOGI SOSIAL EKONOMI

2013· article· en· W2313664757 on OpenAlexaff
Iwan Rudiarto, Wiwandari Handayani, Bitta Pigawati, Pangi Pangi

Bibliographic record

VenueJurnal Tataloka · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMetropolitan areaGeographyFontDescriptive statisticsSocioeconomicsSociologyComputer scienceArchaeologyStatistics

Abstract

fetched live from OpenAlex

Peri-urban can be understood as an area mostly rural located in the surrounding urban center which also has obvious urban character. This paper aims to assess the socio-economic development of Peri-Urban Areas (PUA) of the Metropolitan Semarang in 1990-2011. Study area covers 295 villages that are included in the delineation of the Metropolitan area of Semarang. They are distributed in four cities/districts, i.e.: Semarang city, Semarang regency, Kendal regency, and Demak regency. Satellite imaginary analysis and Geographic Information System (GIS) analysis including overlay analysis, buffer and distance analysis, and descriptive spatial analysis were applied for the analysis. The analysis results show that the PUA of metropolitan Semarang has undergone changes and shifts in socio-economic conditions of rural significant to urban areas. In conclusion, the existence of PUA has led to the blurring of the distinction between rural and urban areas which are not simply dichotomized. Integrated development policies are very essential for more balanced urban development in Semarang Metropolitan region.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.143
Threshold uncertainty score0.480

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1430.023

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 head0.021
GPT teacher head0.202
Teacher spread0.181 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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