The Implementation of Police Reform in Bosnia and Herzegovina: Analysing UN and EU Efforts1
Bibliographic record
Abstract
This article analyses the role of the main international actors involved in the implementation of police reform in post-conflict Bosnia and Herzegovina, notably that of the UN and the EU. Despite considerable efforts and resources deployed over 17 years, the implementation of police reform remains an ‘unfinished business’ that demonstrates the slow pace of implementing rule of law reforms in Bosnia’s post-conflict setting, yet, in the long-term, remains vital for Bosnia’s stability and post-conflict reconstruction process. Starting with a presentation of the status of the police before and after the conflict, UN reforms (1995–2002) are first discussed in order to set the stage for an analysis of the role of the EU in the implementation of police reform. Here, particular emphasis is placed on the institution-building actions of the EU police mission in Bosnia and Herzegovina deployed on the ground for almost a decade (2003-June 2012). The article concludes with an overall assessment of UN and EU efforts in post-conflict Bosnia and Herzegovina, including the remaining challenges encountered by the EU on the ground, as the current leader to police reform implementation efforts. More generally, the article highlights that for police reform to succeed in the long-term, from 2012-onwards, the EU should pay particular attention to the political level, where most of the stumbling blocks for the implementation of police reform lie.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".