Top 5 most viewed and downloaded datasets and other updates from the Justice Hub community.
Top 5 most viewed and downloaded datasets and other updates from the Justice Hub community.
Discussions around Budgets for Justice
Continuing our work on the Budgets for Justice platform to better understand budget data, we collaborated with Civis to conduct a series of discussions with community members. In these sessions, we discussed the budgeting process for the law and justice sector and how we can analyse budgets for legal aid, judicial infrastructure, correctional homes, etc. The conversations can now be accessed at these links:
Justice Hub - In Numbers
It’s been a year since we launched the Justice Hub. Over this period, we have added more than 150 datasets and saw more than 300 user registrations and around 3300 file downloads. We have compiled more such insights in our latest blog Justice Hub - In numbers.
Top 5 most viewed and downloaded Datasets
Cause Lists from the National Companies Law Tribunal (NCLT) Feb 2018 - Jan 2020 - Link
Background of Indian Supreme Court Judges - Link
Data4Justice - Unpacking Judicial Data to Track Implementation of the POCSO Act in Assam, Delhi & Haryana - Link
Justices of the Supreme Court of India (1950-2019) - Link
Indian Kanoon Statistics - Link
We are now working to develop a dashboard for data contributors where they will be able to access a few key metrics related to the datasets they have uploaded on the Justice Hub.
Gender Data Classifier by Development Data Lab
Last month, DevDataLab launched “The Gender Classifier for Indian Names”. Using this tool, you can find the probability that a particular name belongs to a male/female. Often such data points are not directly available and manually coding such variables is error-prone and takes a lot of time.
We wanted to use this tool on the data which was collected during the Summer of Data Initiative. For each judge, a total of 47 data points (including gender) were collected. We wrote an R script to compare the gender data we collected with the gender labels generated by the tool.
Here are the results:
The tool generated similar labels for 95% (1,011 out of 1,059) of the judges tagged as Males whereas, for judges tagged as Females, 87% (62 out of 71) of the gender labels matched. This exercise also helped us identify areas where we can improve our data collection processes, like standardising the names (using full names instead of initials, etc) wherever we can.
Thanks to the team at DevDataLab for releasing an open version of this tool. To know more about why and where they used this, refer to their paper titled - In-group bias in the Indian judiciary: Evidence from 5 million criminal cases
The High Court Privacy Tracker by CCG - NLU
The Centre for Communication Governance at NLU Delhi recently updated the High Court Privacy Tracker. The tracker is a resource consisting of decisions on the right to privacy passed by all High Courts in India. Access here: http://bit.ly/ccg-hc-tracker
Data Source - Annual Reports released by High Courts
Recently, the Orissa High Court released a report which contains a detailed evaluation of the High Court and the State’s lower judiciary. Such reports are important data sources to know more about the performance and functioning of courts but there are very few High Courts that publish them. The High Courts of Madras came out with its annual report for 2020 last year but haven’t released one for 2021 yet.
Read this article by Prashant Reddy T and Chitrakshi Jain to know more about the report released by the Orissa High Court. The report is also available on the Justice Hub.
Do let us know if you’re aware of such reports published by other High Courts. You can also upload them directly on the Justice Hub.
We look forward to your feedback on how we can make the Justice Hub much more accessible and useful for the community. If you have any ideas or suggestions about the newsletter, please write to us at info@justicehub.in. You can also DM us on Twitter.