Determination of the Center for Economic Growth in Surakarta City, Indonesia: Geospatial Approach
Bibliographic record
Abstract
Regarding the case of urban areas, especially in the developing city of Surakarta, of course it cannot be separated from the problem of regional development, especially those related to development inequality, so that determining the center point is the most important thing to do.The purpose of this study is to identify areas in Surakarta that have the potential to become central places.Quantitative approach is applied by analysis of marshall centrality index, scalogram, and gravity index as analytical tools.The results showed that Banjarsari Subdistrict has the potential to as a central place in Surakarta City which has 22 types of service facilities and a total of 5177 units.This affects the strength of spatial interaction between subdistricts in Surakarta City.The highest spatial interaction value is Banjarsari Sub-district with Laweyan of 1,358,589,502 and the lowest is Banjarsari Sub-district with Serengan of 393,687,919.These results can be a consideration for local governments to determine the direction of regional development.By optimizing the central places, the problem of development inequality and uneven distribution of facilities in Surakarta City can be avoided and resolved optimally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".