added legislation and regs to readme
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README.md
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@@ -15,7 +15,7 @@ Bulk open-access helps avoid asymmetrical access-to-justice and amplification of
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results when commercial actors leverage proprietary
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legal datasets for profit -- a particular concern in the border control setting.
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The Canadian Legal Data dataset includes the unofficial
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decisions at the federal level. It can be used for legal analytics (i.e. identifying patterns in legal
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decision-making), to test ML and NLP tools on a bilingual dataset of Canadian legal materials, and to
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pretrain language models for various tasks.
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- SST: Full text of Social Security Tribunal of Canada decisions, baed on the Refugee Law Lab's [Social Security Tribunal Bulk Decisions Dataset](https://refugeelab.ca/bulk-data/sst/) (2013 – present) (updated Apr 1 2024)
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### Data Fields
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- year (int32): Year of the document date, which can be useful for filtering
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- name (string): Name of the document, typically the style of cause of
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- language (string): Language of the document, "en" for English, "fr" for French, "" for no language specified
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- document_date (string): Date of the document
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- source_url (string): URL where the document was scraped and where the official version can be found
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### Curation Rationale
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The dataset includes all the [Bulk Legal Data](https://refugeelab.ca/bulk-data) made publicly available by
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the Refugee Law Lab. The Lab has focused on federal courts (e.g. Supreme Court of Canada, Federal Court of
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Appeal, Federal Court)
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immigration and refugee law, which is the main area of interest of the Lab, operates mostly at the federal level.
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### Source Data
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### Personal and Sensitive Information
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Documents may include personal and sensitive information. All documents have been published online or
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otherwise released publicly by the relevant court or tribunal. While the open court principle mandates
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that court (and some tribunal) materials be made available to the public, there are privacy risks when these
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materials become easily and widely available. These privacy risks are particularly acute for marginalized groups,
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including refugees and other non-citizens whose personal and sensitive information is included in some of the
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documents in this dataset. For example, imagine a repressive government working with private data aggregators to
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collect information that is used to target families of political opponents who have sought asylum abroad.
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One mechanism used to try to achieve a balance between the open court principle
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and privacy is that in publishing
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search engines from indexing the documents. Users of this data are required to do the same.
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### Non-Official Versions
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### Other Known Limitations
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Publicly available court and tribunal decisions are not a representative sample of legal decision-making -- and in some cases may reflect
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significantly skewed samples. To give one example, the vast majority of Federal Court judicial reviews of refugee determinations involve negative
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first instance decisions even thought most first instance decisions are positive (this occurs because the government seldom applies for judicial
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reviews of positive first instance decisions whereas claimants frequently apply for judicial review of negative decisions). As such, generative models
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built partly on this dataset risk amplifying negative refugee decision-making (rather than more common positive refugee decision-making).
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legal datasets may be skewed, users of this dataset are encouraged to collaborate with or consult domain experts.
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## Additional Information
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results when commercial actors leverage proprietary
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legal datasets for profit -- a particular concern in the border control setting.
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The Canadian Legal Data dataset includes the unofficial text of legislation, regulations, and thousands of court and tribunal
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decisions at the federal level. It can be used for legal analytics (i.e. identifying patterns in legal
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decision-making), to test ML and NLP tools on a bilingual dataset of Canadian legal materials, and to
|
21 |
pretrain language models for various tasks.
|
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|
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- SST: Full text of Social Security Tribunal of Canada decisions, baed on the Refugee Law Lab's [Social Security Tribunal Bulk Decisions Dataset](https://refugeelab.ca/bulk-data/sst/) (2013 – present) (updated Apr 1 2024)
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#### Legislation & Regulations
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- LEGISLATION-FED: Text of Federal legislation in the [Consolidated Acts](https://laws-lois.justice.gc.ca/eng/acts/) maintained by the Federal Department of Justice, as reproduced in the Refugee Law Lab's [Federal Bulk Legislation Dataset](https://refugeelab.ca/bulk-data/legislation-fed/) (updated May 13 2024)
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- REGULATIONS-FED: Text of Federal legislation in the [Consolidated Regulations](https://laws-lois.justice.gc.ca/eng/regulations/) maintained by the Federal Department of Justice, as reproduced in the Refugee Law Lab's [Federal Bulk Regulations Dataset](https://refugeelab.ca/bulk-data/regulations-fed/) (updated May 13 2024)
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### Data Fields
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- year (int32): Year of the document date, which can be useful for filtering
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- name (string): Name of the document, typically the style of cause of cases and the short title for legislation and regulations
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- language (string): Language of the document, "en" for English, "fr" for French, "" for no language specified
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- document_date (string): Date of the document (yyyy-mm-dd)
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- source_url (string): URL where the document was scraped and where the official version can be found
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### Curation Rationale
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The dataset includes all the [Bulk Legal Data](https://refugeelab.ca/bulk-data) made publicly available by
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+
the Refugee Law Lab. The Lab has focused on federal law and regulations, federal courts (e.g. Supreme Court of Canada, Federal Court of
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Appeal, Federal Court) and federal administrative tribunals (e.g. Immigration and Refugee Board) because
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immigration and refugee law, which is the main area of interest of the Lab, operates mostly at the federal level.
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### Source Data
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### Personal and Sensitive Information
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Documents may include personal and sensitive information. All documents have been published online or
|
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+
otherwise released publicly by the relevant government body, court or tribunal. While the open court principle mandates
|
126 |
+
that court (and some tribunal) materials be made available to the public, there are privacy risks when some of these
|
127 |
materials become easily and widely available. These privacy risks are particularly acute for marginalized groups,
|
128 |
including refugees and other non-citizens whose personal and sensitive information is included in some of the
|
129 |
documents in this dataset. For example, imagine a repressive government working with private data aggregators to
|
130 |
collect information that is used to target families of political opponents who have sought asylum abroad.
|
131 |
One mechanism used to try to achieve a balance between the open court principle
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+
and privacy is that in publishing court documents in this dataset, the relevant courts and tribunals prohibit
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search engines from indexing the documents. Users of this data are required to do the same.
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### Non-Official Versions
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### Other Known Limitations
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Legislation and regulations do not include tables, annexes or schedules. Original sources should be consulted if these are relevant.
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Publicly available court and tribunal decisions are not a representative sample of legal decision-making -- and in some cases may reflect
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significantly skewed samples. To give one example, the vast majority of Federal Court judicial reviews of refugee determinations involve negative
|
180 |
first instance decisions even thought most first instance decisions are positive (this occurs because the government seldom applies for judicial
|
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reviews of positive first instance decisions whereas claimants frequently apply for judicial review of negative decisions). As such, generative models
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+
built partly on this dataset risk amplifying negative refugee decision-making (rather than more common positive refugee decision-making).
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+
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Due to the ways that
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legal datasets may be skewed, users of this dataset are encouraged to collaborate with or consult domain experts.
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## Additional Information
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