EU Considerations on New Protection of Whistleblowers
Bibliographic record
Abstract
Without some of the important information brought into light by whistleblowers, many current scandals would not have occurred. If whistleblowing is brought into the public domain, it can introduce a previously unforeseen and incorrigible milestone in the biography of whistleblowers, leading to financial loss, loss of work, impact on private life, and even health. Even in situations where the whistleblower acts in good faith, he or she runs the risk of being publicly judged and having the personal reputation tarnished by lack of protection. The persons who have reported wrongdoing may even be driven to complete isolation or pay with their lives or those of their families. In view of this, the European Union has foreseen a better protection for whistleblowers in a new directive, which is to be implemented through a trilateral whistleblower system. The main new feature of the European Whistleblower Protection Directive is the obligation to establish internal whistleblower channels for legal entities in the public and private sectors with at least 50 or more employees. In the public sector, Member States may exempt cities with fewer than 10 000 inhabitants or fewer than 50 employees working in the public body from the obligation to establish whistleblowing channels. If the report to the company or public body is not successful, the whistleblower may report to the press. European legislators had until December 2021 to transpose the provisions of this directive into national whistleblower protection regulations. To date, not all States have accomplished this task.
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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 | 0.038 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.057 | 0.018 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".