A data driven approach to evaluating and improving judicial decision-making: statistical analysis of the judicial review of refugee cases in Australia

Daniel Ghezelbash, Keyvan Dorostkar, Shannon Walsh

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

This article presents analysis of a database of over 6,700 applications for judicial review of refugee cases in the Federal Circuit and Family Court of Australia. The data reveals that the rate at which applications for judicial review are accepted by the Court varies widely based on the judge who hears the case and a number of other factors. While our findings are not necessarily a matter for concern, we argue that they do raise questions around the potential influence of cognitive and social biases in judicial decision-making, as well as in relation to the case management and resourcing of the Court. Drawing on recent research in the field of cognitive and behavioural sciences, we outline how statistics of the nature collected in our study could inform interventions and reforms aimed at addressing such biases and increase public confidence in the judicial system.

Original languageEnglish
Pages (from-to)1085-1123
Number of pages39
JournalUniversity of New South Wales Law Journal
Volume45
Issue number3
Publication statusPublished - Aug 2022

Keywords

  • Computational methods
  • Judicial Review
  • Statistics: Refugee Law

Fingerprint

Dive into the research topics of 'A data driven approach to evaluating and improving judicial decision-making: statistical analysis of the judicial review of refugee cases in Australia'. Together they form a unique fingerprint.

Cite this