license: cc-by-nc-4.0
language:
- en
- fr
size_categories:
- 10K<n<100K
Refugee Law Lab: Canadian Legal Data
Dataset Description
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Dataset Summary
The Refugee Law Lab supports bulk open-access to Canada legal data to facilitate research and advocacy, focusing on federal law and law relating to refugees and other people on the move. Bulk open-access helps avoid asymmetrical access-to-justice and amplification of marginalization that results when commercial actors leverage proprietary legal datasets for profit -- a particular concern in the border control setting.
This dataset includes the unofficial full text of thousdands of court and tribunal decisions at the federal level. It can be used for legal analytics (e.g. identifying patterns in legal decision-making), to test ML and NLP tools on a bilingual (French and English) dataset of Canadian legal materials, and to pretrain language models.
Languages
Many documents are available in both English and French. Some are only available in one of the two languages.
Dataset Structure
Data Instances
- SCC: Full text of all Supreme Court of Canada decisions, based on the Refugee Law Lab's Supreme Court of Canada Bulk Decisions Dataset (1877 – 2023)
- FCA: Full text of all Federal Court of Appeal (Canada) decisions that have been given a neutral citation, based on the Refugee Law Lab's Federal Court of Appeal Bulk Decisions Dataset (2001-2023)
- FC: Full text of all Federal Court (Canada) decisions that have been given a neutral citation, based on the Refugee Law Lab's Federal Court Bulk Decisions Dataset (2001-2023)
Data Fields
citation1 (string): Legal citation for the document (neutral citation where available)
citation2 (string): For some documents multiple citations are available (e.g. for some periods the Supreme Court of Canada provided both official reported citation and neutral citation)
data_instance (string): Name of the data instance (e.g. "SCC", "FCA", "FC", etc)
year (int32): Year of the document date, which can be useful for filtering
name (string): Name of the document, typically the style of cause of a case
language (string): Language of the document, "en" for English, "fr" for French
document_date (string): Date of the document, typically the date of a decision (yyyy-mm-dd)
source_url (string): URL where the document was scraped and where the official version can be found
scraped_timestamp (string): Date the document was scraped (yyyy-mm-dd)
unofficial_text (string): Full text of the document (unofficial version, for official version see source_url)
other (string): Field for additional metadata in JSON format, currently a blank string for most datasets
Data Splits
The data has not been split, so all files are in the train split. If splitting for training/validation, some thought should be given to whether it is necessary to limit to one language or to ensure that both English and French versions of the same documents are put in the same split.
Dataset Creation
Curation Rationale
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Source Data
Initial Data Collection and Normalization
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Who are the source language producers?
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Annotations
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
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Licensing Information
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Citation Information
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Contributions
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