Problem drug use in the Prague's quarter without functioning specialised harm reduction programme
Bibliographic record
Abstract
The bachelor paper undertakes a topic of problem drug use, it's development, nature, range of consequences for individuals and the society. It's focused onrecentsituation inproblem drug use in the Czech Republic and Prague, onwork of low-threshold services for problem drug users, drug policy of capital city and particular part of the city. The aim of the research was to analyse the situation of problem drug use in Prague's quarter Michle, where no specialized low-threshold program for drug users is operating. The intention was to find out whether problem drug use exists in the area, what is it's prevalence, patterns, specifics, and whether the low-threshold program is needed. The Rapid Assessment and Response methodologywas used as a method of data collection and analysis - analysis of available data and materials (annual reports of organizations, materials of Prague drug policy) and semi-structured interviews with key informants (problem drug users, representatives of institutions, workers of Prague low-threshold services, locals and informants in the service sector). The views of the overwhelming majority of respondents agree, support and complement each other. Problem drug use is occurring in the Michle district and has its own characteristics (a high proportion of users of buprenorphine, less...
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".