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Case study in investigative interpretation of cell-site observations: Estimating locations of mobile telephones in the absence of survey data.

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What should a forensic practitioner's likelihood ratio be? II.

Geoffrey Stewart Morrison1

  • 1Forensic Speech Science Laboratory, Centre for Forensic Linguistics, Aston University, Birmingham, England, United Kingdom; Department of Linguistics, University of Alberta, Edmonton, Alberta, Canada; Isaac Newton Institute for Mathematical Sciences, Cambridge, England, United Kingdom.

Science & Justice : Journal of the Forensic Science Society
|November 28, 2017
PubMed
Summary

Forensic practitioners should report precise strength of evidence. This approach enhances objectivity, transparency, and scientific validity in court, moving beyond subjective probability interpretations for better legal evidence evaluation.

Keywords:
AccuracyBayes factorLikelihood ratioPrecisionReliabilityValidity

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Area of Science:

  • Forensic Science
  • Probability Theory
  • Statistical Modeling

Background:

  • The debate on reporting precision in forensic evidence strength is ongoing.
  • Sole reliance on subjectivist probability is seen as counterproductive for scientific validity in legal settings.
  • Current methods may lack sufficient objectivity, transparency, and replicability.

Purpose of the Study:

  • To propose an improved approach for evaluating the strength of forensic evidence.
  • To maximize empirical performance, objectivity, and transparency in forensic analysis.
  • To constrain and make overt subjective judgments in forensic evaluations for judicial scrutiny.

Main Methods:

  • Utilizing procedures that maximize empirically demonstrable performance.
  • Enhancing objectivity through transparency, replicability, and minimizing cognitive bias.
  • Constraining subjective judgments to early stages of analysis (hypothesis selection, data use, modeling).

Main Results:

  • Constraining subjective judgments reduces cognitive bias and increases transparency.
  • Bayes factors and frequentist likelihood ratios offer comparable objectivity when using appropriate priors/data.
  • Both methods, when adjusted for imprecision, tend to moderate the strength of evidence towards a neutral value (1).

Conclusions:

  • A practical solution involves procedures that account for imprecision by adjusting Bayes factors or likelihood ratios towards 1.
  • This approach enhances the logical correctness and scientific validity of forensic evidence presented in court.
  • Empirical demonstration of performance should guide the selection of specific procedures for evidence evaluation.