Propose a Model of Urban Landscape Management Deal with City Vandals: A Case Study of 20th District of Tehran
Bibliographic record
Abstract
Vandalism is one of the hidden results of the rise of modernism that appearance of this phenomenon can be seen in city centers, schools, sports club, etc. in abundance. And today in urban communities is considered as a serious problem that compromises safety and security of urban communities. Destruction of the urban landscapes by the vandals and loss of interests of citizens in the case of the city face that creates confusion and chaos of urban landscape is not a new problem. And at least in the last three decades considered by the social activist groups and NGOs, environmental scientists, artists, city managers and ordinary people directly and indirectly. It exists convergence and consensus on the desirability of merging the face of the city and reducing urban landscape and urban landscapes as part of a person's identity and is known aspect of human existence. The purpose of this article is providing a model of urban landscape management in dealing with urban vandal from the perspective of residents and administrators. Using existing literature, beginning some management indicators to assess the effects of mining and based on required data were collected through questionnaires from district 20 in Tehran. Study, methods that fits the type of data model is used SWOT and statistical methods to analyze data without parameters. The results show that the effects of vandalism in the considered area were been and can be customized according to the features and functionality and urban potential in this area and by applying strategic planning, according to the aforementioned factors and in the shadow of integrated management sustainable development in order to reduce the effects of destruction in this region. It also seems to be the best kind of theory about urban management in the region, a new theory or system. And in 20th District management model in order to deal with urban vandalism attention to the planners and policy makers in different dimensions is considered. As well as monitoring and planning should be limited to the initial phase and policies But also in the design, implementation and maintenance of urban spaces, urban furniture, etc. should also be considered And in this respect also must be careful.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".