Datasets:

refugee-law-lab
/

canadian-legal-data

@@ -45,6 +45,8 @@ the Refugee Law Lab's [Federal Court Bulk Decisions Dataset](https://refugeelab.
 - 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)
 - 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
@@ -59,8 +61,6 @@ the Supreme Court of Canada provided both official reported citation and neutral
 - unofficial_text (string): Full text of the document (unofficial version, for official version see source_url)
-- dataset (string): Name of the data instance (e.g. "SCC", "FCA", "FC", etc)
 - other (string): Field for additional metadata in JSON format, currently a blank string for most datasets
 ### Data Languages
@@ -155,7 +155,7 @@ religion, disability, socio-economic class, etc.
 Publicly available court and tribunal decisions are not a representative sample of legal decision-making -- and in some cases may reflect
 significantly skewed samples. To give one example, the vast majority of Federal Court judicial reviews of refugee determinations involve negative
-first instance decisions even thought most first instance decisions are positive (this occurs because the government seldom apply for judicial
 reviews of positive first instance decisions whereas claimants frequently apply for judicial review of negative decisions). As such, generative models
 built partly on this dataset risk amplifying negative refugee decision-making (rather than more common positive refugee decision-making). Due to the ways that
 legal datasets may be skewed, users of this dataset are encouraged to collaborate with or consult domain experts.

 - 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)
+- dataset (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
 - 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 Languages
 Publicly available court and tribunal decisions are not a representative sample of legal decision-making -- and in some cases may reflect
 significantly skewed samples. To give one example, the vast majority of Federal Court judicial reviews of refugee determinations involve negative
+first instance decisions even thought most first instance decisions are positive (this occurs because the government seldom applies for judicial
 reviews of positive first instance decisions whereas claimants frequently apply for judicial review of negative decisions). As such, generative models
 built partly on this dataset risk amplifying negative refugee decision-making (rather than more common positive refugee decision-making). Due to the ways that
 legal datasets may be skewed, users of this dataset are encouraged to collaborate with or consult domain experts.