Court, Judges and the Pandemic: Computational Legal Insights from the Ontario Court of Appeal Corpus 2008-2021

Appellate courts occupy a unique position. They are the final instance for most litigants guiding lower courts but they are also a gateway to the Supreme Court. This dual role calls for special scrutiny and analysis. Yet, data and analysis of appeal courts remains scarce especially compared to apex courts. This article fills part of this gap relating to the Ontario Court of Appeal. It introduces a new dataset of its decisions between 2008-2021 consisting of both metadata, such as outcomes per decision, and the decision full text, which can be mined through natural language processing techniques. Aside from presenting the dataset, the paper uses novel data science approaches to trace the practice of the Court over time, to dissect the decision patterns of its judges, and to assess how the pandemic shock impacted the Court. It finds, amongst others, that the Court has been stable in its decision patterns, but that decisions have grown longer; it also shows that some judges render harsher decisions than others, and it illustrates how the pandemic created instant precedent. We hope that the new dataset and corpus will spur further research on the Ontario Court of Appeal.