The Institute of Staff Criminologists (Criminal Analysts): Foreign Experience and Prospects of Its Introduction in the System of Crime Prevention in the Russian Federation
Bibliographic record
Abstract
The authors examine the possibilities of the criminological analysis of criminal situation and show the value of using modern information systems to analyze and predict crimes for the improvement of the crime prevention work of internal affairs’ bodies. They study the analytical methods that make crime prevention more productive and the key software used for criminal analysis. The article presents the results of studying the work of criminal analysts in various legal systems (the UK, the USA, Canada, South Korea, New Zealand). It contains the data of an experts’ survey conducted in June 2017. The experts were 100 employees of investigation departments, centers of counteracting extremism, economic security and corruption counteraction, employees of organization and analytical departments of the Chief Directorate of Russian Ministry of the Interior in Moscow and Moscow Region. The analysis of the work of criminal analysts in other countries and the results of the survey of experts from law enforcement bodies are used to determine the prospects of introducing the institute of staff criminologists in the crime prevention system of the Russian Federation, to develop an algorithm of criminological support in Russian internal affairs’ bodies and to outline the prospective spheres of work for staff criminologists (criminal analysts). The authors conclude that the effectiveness of the work of Russian internal affairs’ bodies on the prevention, suppression and detection of crimes could be considerably improved through the introduction of modern means and methods of criminal analysis that are currently actively used by the police of some countries. They present a conceptually new approach to the criminological support of the work of internal affairs’ bodies based on the cumulative analysis of the current legislative base of the Russian Federation, the existing theoretical approaches and the experience of organizing the work of criminal analysts in other countries. The authors express their confidence that quality and professional work of using means and methods of crime prediction could help optimize the use of available resources and authority of law enforcement bodies and, consequently, either reduce the costs of law enforcement or use the available budgets more effectively.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".