a2aj/canadian-case-law

A2AJ Canadian Case Law

Last updated: 2026-05-31 Maintainer: Access to Algorithmic Justice (A2AJ)

Dataset Summary

The A2AJ Canadian Case Law dataset provides bulk, open-access full-text decisions from Canadian courts and tribunals. Each row corresponds to a single case and contains the English and French versions of the decision where both are publicly available. The project builds on an earlier version that was maintained by the Refugee Law Lab (RLL) and is now maintained by A2AJ, a research project co-hosted by York University's Osgoode Hall Law School and Toronto Metropolitan University's Lincoln Alexander School of Law. The dataset is intended to support empirical legal research, legal-tech prototyping, and language-model pre-training in the public interest—especially work that advances access to justice for marginalised and low-income communities.

Dataset Structure (~ 222k cases)

Code	Court / Tribunal / Reporter	First document - Last document	Rows
SCC	Supreme Court of Canada	1877-01-15 – 2026-05-29	10,882
FCA	Federal Court of Appeal	2001-02-01 – 2026-05-29	7,764
BCCA	British Columbia Court of Appeal	1999-01-04 – 2026-05-29	14,564
ONCA	Ontario Court of Appeal	1998-06-08 – 2026-05-28	23,854
NSCA	Nova Scotia Court of Appeal	1993-01-04 – 2026-05-26	4,720
YKCA	Yukon Court of Appeal	2000-05-15 – 2026-04-27	275
FC	Federal Court	2001-02-01 – 2026-05-29	35,520
TCC	Tax Court of Canada	2003-01-21 – 2026-05-27	8,060
CMAC	Court Martial Appeal Court	2001-01-19 – 2026-05-19	154
BCSC	Supreme Court of British Columbia	2000-01-04 – 2026-05-28	51,788
NSSC	Nova Scotia Supreme Court	2001-01-04 – 2026-05-26	9,151
NSPC	Nova Scotia Provincial Court	2001-01-15 – 2026-05-26	1,599
NSFC	Nova Scotia Family Court	2001-02-02 – 2023-11-06	323
NSSM	Nova Scotia Small Claims Court	2001-08-30 – 2026-03-20	1,648
CHRT	Canadian Human Rights Tribunal	2003-01-10 – 2026-05-11	1,140
CIRB	Canada Industrial Relations Board	1995-12-08 – 2026-04-30	1,169
CITT	Canadian International Trade Tribunal	1980-01-01 – 2026-05-28	5,301
CT	Competition Tribunal	2000-02-17 – 2026-05-19	623
FPSLREB	Federal Public Sector Labour Relations and Employment Board	2003-01-03 – 2026-04-23	3,425
OHSTC	Occupational Health and Safety Tribunal Canada	1992-01-09 – 2025-03-06	811
OIC	Information Commissioner of Canada	2019-08-26 – 2026-03-27	323
PSDPT	Public Service Disclosure Protection Tribunal	2011-06-10 – 2025-05-21	29
RAD	Refugee Appeal Division (IRB)	2013-02-19 – 2025-08-11	14,122
RPD	Refugee Protection Division (IRB)	2002-07-16 – 2020-12-14	6,729
RLLR	Refugee Law Lab Reporter (RPD, IRB)	2019-01-07 – 2024-12-13	927
SST	Social Security Tribunal	2013-03-08 – 2026-05-13	17,705

Note: Counts are approximate and will drift as the dataset is updated.

Data Fields

Field	Type	Description
dataset	string	Abbreviation identifying the court/tribunal (see above)
citation_en / citation_fr	string	Neutral citation in English / French
citation2_en / citation2_fr	string	Secondary citation(s) where available
name_en / name_fr	string	Style of cause
document_date_en / document_date_fr	datetime64[ns, UTC]	Decision date
url_en / url_fr	string	Source URL for the official online version
scraped_timestamp_en / scraped_timestamp_fr	datetime64[ns, UTC]	Timestamp when the page was scraped
unofficial_text_en / unofficial_text_fr	string	Full unofficial text of the decision
upstream_license	string	License terms from the source court/tribunal
Missing values are represented as empty strings ("") or NaN.

Data Languages

Where availble, rows include both English and French texts. Where only one language is published, the fields for the other language are empty. ### Data Splits All rows are provided in a single train split.

Data Loading

from datasets import load_dataset
import pandas as pd
# load decisions for a specific court / tribunal (e.g. Supreme Court of Canada)
cases = load_dataset("a2aj/canadian-case-law", data_dir = "SCC", split="train")
## ALTERNATIVELY
## load the entire corpus
# cases = load_dataset("a2aj/canadian-case-law", split="train")
# covert to df
df = cases.to_pandas()
df.head(5)

The dataset is also offered in Parquet format for fast local use. Files are in subfolders with the court/tribunal names.

Dataset Creation

Curation Rationale

Building on the RLL's earlier bulk-data programme, A2AJ is collecting and sharing Canadian legal data to: * democratise access to Canadian jurisprudence; * enable large-scale empirical legal studies; and * support responsible AI development for the justice sector. We scrape data only where we are permitted to do so by terms of service of websites that host the data. We also obtain some additional data directly from courts and tribunals. ### Source Data & Normalisation Cases are scraped directly from the official websites of the respective courts and tribunals, or is obtained directly from the tribunals through email or other distruction processes. Where possible, text is stored verbatim with minimal normalisation (e.g. HTML → plain text, whitespace cleanup). ### Personal & Sensitive Information Court and tribunal decisions can contain sensitive personal information. Although all documents are already public, easy bulk access increases privacy risk—particularly for refugees, criminal-justice-involved persons and other marginalised groups. Users who reproduce the data from this dataset are responsible for complying with relevant privacy laws, as well as other laws relating to disseminating information such as publication bans. ### Non-Official Versions & Disclaimer The texts here are unofficial copies. For authoritative versions, consult the URLs in url_en / url_fr. ### Non-Affiliation / Endorsement A2AJ and the production of this dataset are not affiliated with, nor endorsed by, the Government of Canada, provincial courts, or the listed tribunals.

Considerations for Using the Data

• Social Impact. Open legal data can reduce information asymmetries but also facilitate surveillance or discriminatory profiling. We encourage downstream users to collaborate with community organisations and ensure that derivative tools advance—rather than undermine—access to justice.
• Bias & Representativeness. Published decisions are not a random sample of disputes. For example, positive administrative decisions are less likely to be appealed and thus under-represented in court records. Models trained on this corpus may therefore skew negative.
• Limitations. The dataset excludes annexes, schedules and appendices that are sometimes attached as separate PDFs. Long historical gaps exist for some courts (e.g. ONCA pre-1990).

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Licensing Information

The code used to create the dataset by the A2AJ and any work on the dataset undertaken by the A2AJ is subject to an open source MIT license. Users must also comply with upstream licenses found in the upstream_license field in the dataset for each document, which reflects the licenses through which the A2AJ obtained the document. These upstream licenses may include limits on commercial use, as well as other limitations. The A2AJ is committed to open source methodologies, and we are actively working to obtain more permissive licenses for this data.

Warranties / Representations

While we make best efforts to ensure the completeness and accuracy of the dataset, we provide no warranties regarding completeness or accuracy. The data were collected through automated processes and may contain errors. Always verify data against the official source.

Dataset Curators

• Sean Rehaag - Co-Diretor, A2AJ
• Simon Wallace - Co-Director, A2AJ
• Contact: a2aj@yorku.ca

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Citation

Sean Rehaag & Simon Wallace, "A2AJ Canadian Case Law" (2025), online: Hugging Face Datasets https://huggingface.co/datasets/a2aj/canadian-case-law (updated 2026).

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Acknowledgements

This research output is supported in part by funding from the Law Foundation of Ontario and the Social Scienes and Humanities Research Council of Canada, by in-kind compute from the Digital Research Alliance of Canada and by adminstrative support from the Centre for Refugee Studies, the Refugee Law Lab, and Osgoode Hall Law School. We also thank the Canadian judiciary and tribunal staff who publish decisions in open formats.