The Myth of Judicial Objectivity: Why Subjectivity is The Only Path to a Transparent Trial
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Abstract
This comment addresses the ‘prior challenge’ in forensic Bayesian modelling, recently highlighted by Anne Ruth Mackor (2026). We argue that the perceived lack of frequency data is not an insurmountable obstacle but a misconception rooted in an outdated view of probability. By adopting a radical subjectivist perspective based on de Finetti’s teachings, we reframe probability as a coherent representation of a decision-maker’s state of knowledge. We advocate for a strict functional separation: forensic experts provide the likelihood ratio based on technical findings, while the court assigns prior odds based on the specific case context. Through sensitivity analysis, we demonstrate that the subjectivity of priors is not a source of arbitrariness but a transparent, auditable mechanism that enhances judicial accountability. Ultimately, the Bayesian model is presented as a logical necessity for preventing miscarriages of justice.Keywords
Bayesian modelling, Forensic science, Subjective probabilityDownloads
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DOI
https://doi.org/10.33115/udg_bib/qf.i11.23268Published
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