Spatial Dispersion and Analysis of Urban Property Crime in Turkey
Bibliographic record
Abstract
In Turkey, the Police Department is responsible for urban crimes and General Command of Gendarmerie for rural crimes. Urban criminal records, for which the Directorate General of Security is responsible, are classified under two headings: crimes against property and crimes against life. The present study first evaluated total criminal data and carried out a dispersion analysis of crime rates per 100 000 people for individual cities. The rate of crimes against property per 100 000 people was then evaluated for individual cities. Classified under crimes against property, theft, seizure, and other crimes were assessed separately and mapped for individual cities. Thus, regions in which crimes against property are concentrated were determined. It was determined that the rates of concentration have increased more in industrialized and urbanized regions. Maps showing the dispersion of crimes against property across cities show that crime rates in Turkey increase from east to west and from the interior to the coa...
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".