Questioni scientifiche e argomentazione delle corti nell'emergenza sanitaria. Una proposta tassonomica
Bibliographic record
Abstract
Il contributo si concentra sul profilo dell’argomentazione giuridica durante il periodo dell’emergenza pandemica, per analizzare se, come ed in quale misura il dato scientifico è stato impiegato nel ragionamento delle corti. In particolare, attraverso l’esame della giurisprudenza della Corte suprema degli Stati Uniti, di alcune corti provinciali del Canada e della Corte costituzionale federale tedesca, si ipotizza una proposta tassonomica, che tiene conto del rilievo delle risultanze scientificamente connotate nelle motivazioni delle rispettive decisioni. Da un lato, la Corte suprema statunitense, con la svolta in chiave marcatamente conservatrice, si colloca sul “gradino” più basso; su una posizione intermedia, si attesta il Canada; dall’altro lato, l’esperienza tedesca rappresenta il momento più alto, in merito alla rilevanza delle valutazioni scientifiche nei passaggi che scandiscono l’argomentazione delle decisioni. The paper focuses on the legal reasoning during the health emergency to analyze whether, how and to what extent scientific evidence was employed by courts in justifying their decisions. In particular, the pandemic litigation of the U.S. Supreme Court, of some Canadian provincial courts and of the German Federal Constitutional Court suggests developing a taxonomic proposal, which takes into account the relevance of scientifically connoted findings in the reasoning of their decisions. On the one hand, the U.S. Supreme Court, with its markedly conservative shift, is on the lowest "rung"; Canadian courts are on an intermediate position; whereas, the German Federal Constitutional Court represents the utmost expression of the interaction between the judicial decision-maker and scientific evidence.
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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 | 0.037 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".