Bibliographic record
Abstract
Since 1989, reforms have sought to align the Romanian post-communist intelligence community with its counterparts in established democracies. Enacted reluctantly and belatedly at the pressure of civil society actors eager to curb the mass surveillance of communist times and international partners wishing to rein in Romania’s foreign espionage and cut its ties to intelligence services of non-NATO countries, these reforms have revamped legislation on state security, retrained secret agents, and allowed for participation in NATO operations, but paid less attention to oversight and respect for human rights. Drawing on democratization, transitional justice, and security studies, this article evaluates the capacity of the Romanian post-communist intelligence reforms to break with communist security practices of unchecked surveillance and repression and to adopt democratic values of oversight and respect for human rights. We discuss the presence of communist traits after 1989 (seen as continuity) and their absence (seen as discontinuity) by offering a wealth of examples. The article is the first to evaluate security reforms in post-communist Romania in terms of their capacity to not only overhaul the personnel and operations inherited from the Securitate and strengthen oversight by elected officials, but also make intelligence services respectful of basic human rights.
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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 | 0.028 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.018 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".