Large City Social and Spatial Segregation in Youth's Opinion
Bibliographic record
Abstract
The article deals with the problem of the socio-spatial segregation of the city as the isolation of social groups in the urban space. As human civilization advances, cities are transformed into "dominant types of settlements", which makes it important to study the phenomena of urban life, including urban social segregation. The major research objective is to analyze the youth' attitudes toward the city as a space of vital activity and to assess the city space segregation of Yekaterinburg. The research methodology combines qualitative and quantitative methods. Methods of collecting primary data were the questionnaire and in-depth interview. 200 young people were questioned at the age of 18 years and older on the basis of the "a sampling in 2015 in the city of Yekaterinburg. Depths interviews with experts (n=15) are applied on purpose to identify main problems of the topic. The investigation has revealed that the city of Yekaterinburg in Russian youth' opinion is divided into specific local units: the core and the periphery. At the same time, the periphery is divided into two large zones: industrial quarter and commune of residence which are located in different parts of the urban space. Two thirds of the respondents are satisfied with their area of residence and 30% of the respondents would like to move to the center of the city. The research has fixed the key issues which exist in the city periphery. The majority of uncontrolled parking lots near residential buildings and transport lines congestion are the main issues of commune of residence. Insufficient territory's cleaning, poor streets lighting and the need for green spaces are the key issues of industrial quarters. The survey has shown that the urban space is divided into three zones: the core (center) with modern buildings of executive housing in which high-income people live, the periphery commune of residence where the middle class lives, and industrial quarters of the periphery where people with lower incomes live. © Published under licence by IOP Publishing Ltd.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".