La pandémie de COVID-19 et le droit européen des droits de la personne : réflexions sur l’application de la Convention européenne des droits de l’homme à l’ère du confinement et des masques obligatoires
Bibliographic record
Abstract
How is the European Convention on Human Rights likely to apply to the many aspects of the current pandemic?As always with novel factual questions, the answer can only be found in a thorough and innovative examination of the case-law of the European Court of Human Rights.We consider firstly the duties of Member States with respect to health issues under the Convention.From this starting point, we will then seek to determine whether the measures adopted by States to limit the spread of the virus should be viewed as the fulfillment of the positive obligation to protect the right to life enshrined in the Convention, or rather as an encroachment on that right because of the many "side-effects" of those measures on the day to day lives of individuals.We will then present two fictional scenarios involving the potential deleterious impact of common measures such as confinement and mandatory masks in the context of the question of how victims might obtain redress from the Court for the alleged violation of certain rights and freedoms protected under the Convention, for example the prohibition against inhumane and degrading treatment, arbitrary detention and discrimination. 1.Le confinement et la discrimination .Le masque comme condition obligatoire au déconfinement : une discrimination indirecte?............
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".