Update README.md

README.md

@@ -16,9 +16,9 @@ results when commercial actors leverage proprietary
 legal datasets for profit -- a particular concern in the border control setting.
 
 The Canadian Legal Data 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 
+decisions at the federal level. It can be used for legal analytics (i.e. identifying patterns in legal 
 decision-making), to test ML and NLP tools on a bilingual dataset of Canadian legal materials, and to 
-pretrain language models.
+pretrain language models for various tasks.
 
 
 ## Dataset Structure
@@ -95,16 +95,16 @@ immigration and refugee law, which is the main area of interest of the Lab, oper
 
 #### Initial Data Collection and Normalization
 
-Details (including links to github repos with code) are available via links for the Refugee Law Lab's 
-Bulk Legal Data page.
+Details (including links to github repos with code) are available via links on the Refugee Law Lab's 
+[Bulk Legal Data](https://refugeelab.ca/bulk-data/) page.
 
 ### Personal and Sensitive Information
 
 Documents may include personal and sensitive information. All documents have been published online or 
 otherwise released publicly by the relevant court or tribunal. While the open court prinple mandates 
-that court (and some tribunal) materials be available to the public, there are privacy risks when these 
+that court (and some tribunal) materials be made available to the public, there are privacy risks when these 
 materials become easily and widely available. These privacy risks are particularly acute for marginalized groups, 
-include refugees and other non-citizens whose personal and sensitive information is included in some of the
+including refugees and other non-citizens whose personal and sensitive information is included in some of the
 documents in this dataset. One mechanism used to try to achieve a balance between the open court principle 
 and privacy is that in publishing the documents in this dataset, the relevant courts and tribunals prohibit 
 search engines from indexing the documents. Users of this data are required to do the same.
@@ -123,15 +123,34 @@ the government of Canada.
 
 ### Social Impact of Dataset
 
-[More Information Needed]
+The Refugee Law Lab recognizes that this dataset -- and further research using the dataset -- raises challenging 
+questions about how to balance protecting privacy, enhancing government transparency, addressing information 
+asymmetries, and building technologies that leverage data to advance the rights and interests of 
+refugees and other displaced people (rather than technologies that 
+[enhance the power of states](https://citizenlab.ca/2018/09/bots-at-the-gate-human-rights-analysis-automated-decision-making-in-canadas-immigration-refugee-system/) 
+to control the movement of people across borders).
+
+More broadly, the Refugee Law Lab also recognizes that considerations around privacy and data protection are complex 
+and evolving. When working on migration, refugee law, data, technology and surveillance, we strive to foreground 
+intersectional understandings of the systemic harms perpetuated against groups historically made marginalized. We 
+encourage other users to do the same.
+
+We also encourage users to try to avoid participating in building technologies that harm refugees and other 
+marginalized groups, as well as to connect with [community organizations](https://www.migrationtechmonitor.com/ways-to-help) 
+working in this space, and to [listen directly](https://www.migrationtechmonitor.com/about-us) to people who are affected by new technologies. 
 
 ### Discussion of Biases
 
-[More Information Needed]
+The dataset reflects many biases present in legal decision-making, including biases based on race, immigration status, gender, sexual orientation, 
+religion, disability, socio-economic class, etc. 
 
 ### Other Known Limitations
 
-[More Information Needed]
+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. Due to the ways that 
+legal datasets may be skewed, users of this dataset are encouraged to collaborate with or consult domain experts.
 
 ## Additional Information
 
@@ -142,8 +161,8 @@ Attribution-NonCommercial 4.0 International ([CC BY-NC 4.0](https://creativecomm
 
 NOTE: Users must also comply with upstream licensing for the [SCC](https://www.scc-csc.ca/terms-avis/notice-enonce-eng.aspx), 
 [FCA](https://www.fca-caf.gc.ca/en/pages/important-notices) & [FC](https://www.fct-cf.gc.ca/en/pages/important-notices) data instances, as 
-well as requests on source urls not to allow indexing of the documents by search engines (so do
-not make the data available in other formats or locations that can be indexed by search engines).
+well as requests on source urls not to allow indexing of the documents by search engines to protect privacy. As a result, users must 
+not make the data available in formats or locations that can be indexed by search engines.
 
 ### Warranties / Representations
 
@@ -159,7 +178,7 @@ Sean Rehaag, Osgoode Hall Law School Professor & Director of the Refugee Law Lab
 
 ### Citation Information
 
-Sean Rehaag, "Refugee Law Lab: Canadian Legal Data" (2023) online: HuggingFace: <https://huggingface.co/datasets/refugee-law-lab/canadian-legal-data>.
+Sean Rehaag, "Refugee Law Lab: Canadian Legal Data" (2023) online: Hugging Face: <https://huggingface.co/datasets/refugee-law-lab/canadian-legal-data>.
 
 ### Acknowledgements