Bibliographic record
Abstract
This study aims to analysis and appreciate the administrative system of street furniture in Korea and to propose the method to improve the system. Street furniture is an important component of street environment, thus to improve the quality of street furniture is essential to improve the overall situation of urban street. The present state of street furniture in Korea shows some problems related to design, function, and so on. These problems are not treated in itself, but treated in relation with its administrative system because the problems are the results of the system. Firstly, there are no integrated organization which can coordinate the overall system dealt with establishment, operation and supervision of street furniture. Second of all, they have no specific guidelines for handling the street furniture. Lastly, there are some differences between public and private facilities and between region which have profitability and one which does not have. Recently, there are some endeavors to improve street furniture including establishment of laws and codes and organization of committee and bureau; however these attempts are nothing but initiative steps. The coordinated street furniture system of Boston and Toronto is a good example. To improve the administrative system of street furniture, first of all, the integrated organization to control overall system should be established, and the specific guideline to make, operate and supervise the street furniture should be prepared. Additionally, it is necessary to have a flexible system to response the diverse urban situation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".