Evaluation of the operational viability of forensic units in Brazil: A hybrid approach based on the BWM and R-TOPSIS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Public security is an area of increasing importance in Brazil, as society requires that public resources are managed more efficiently and effectively. Criminalistics is an integral and vital part of the Brazilian public security system and requires new management tools to optimize human resources, equipment, and facilities allocation. Faced with a challenging scenario of budgetary constraints in several areas in public administration, the search for innovative methods should be a priority for the forensic service sector managers. The current article presents a multicriteria decision model to evaluate the operational viability of 23 forensic units within the Federal Police of Brazil (PF). The framework used the hybrid approach BWM and R-TOPSIS. The proposed model led to the complete ranking of 23 local forensic units. Amongst the last positions in the ranking, it was possible to recommend merging or shutting down some units. The sensitivity analysis performed did not show abrupt variations in the original positions, confirming the robustness of the proposed solution. It was concluded that the model allowed resources optimization whilst not compromising the quality of the services provided to society.
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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 | 0.003 | 0.001 |
| 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) | 0.000 | 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 it