The Sense of Security of the Residents of the Borderland of Cieszyn Silesia Based on the Example of the City of Czech Cieszyn
Bibliographic record
Abstract
The article analyses the issue of the sense of public security of the residents of the borderland of Cieszyn Silesia based on the example of Czech Cieszyn, a border city. Supported by research, it also presents an evaluation of police work in the city’s communities. The research was conducted in Czech Cieszyn in 2017. The research shows the current state of security and the sense of the security of the city’s inhabitants. The research mainly focuses on the level of security of Czech Cieszyn’s residents and communities occupying the borderlands of Cieszyn Silesia and the evaluation of the image of the Police of the Czech Republic. The research has adopted the diagnostic poll method in the form of a survey for which a questionnaire has been created. The analysis of the research outcome allows peculiar correlations to be identified, such as sex, age, education level, professional activity etc., time of day, the sense of security in each city quarter. The research indicates the presence of an optimistic trend of a rather high, subjectively experienced sense of security of the city’s residents. Since the citizens’ sense of security is largely dependent on the visible uniformed presence of the police patrolling the city, the research also includes the issue of the society’s satisfaction with local police service. The interviewees graded the competence, courteousness and communication skills of the officers along with their willingness to assist the residents. In general, the officers’ performance is good according to the community of Czech Cieszyn. The article ends with a conclusion along with a positive statement that the city council and the police have undertaken and have been already taking action to prevent the most undesirable threats.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".