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How do we quantitatively analyse legal-judicial data?
Jurimetrics is the use of empirical methods to analyse legal matters. In jurimetric studies, researchers develop legal indicators that help evaluate the implementation of a law, the efficiency of a court etc. These are similar to KPIs, but measure the performance of judicial systems.
In this newsletter, we explore a few case studies hosted on JusticeHub that deal with Jurimetrics to quantitatively educate us about judicial systems.
Jurimetric studies that measure the efficiency of courts
We seek an efficient judicial system in which justice gets delivered in a reasonable time. But what metrics should we monitor to build such a judicial system? The following studies help us answer this question.
VIDHI Centre for Legal Policy analysed the caseload of the Supreme Court (SC) using the data from SC Causelists in 2019 and 2020. The datasets and analyses are hosted on JusticeHub here. JusticeHub also hosts the cause list data of National Companies Law Tribunals. A similar analysis on it would help us understand how burdened these tribunals are.
Such datasets when developed for all courts in India would help us monitor the caseload of the Indian judiciary and make decisions on the allocation of judicial resources.
We have also conducted a webinar with the VIDHI team on the analysis of SC caseload data. You can check it for more inspiration
A few other studies hosted on JusticeHub on the efficiency of courts in India are:
A quantitative analysis of the Indian Supreme Court’s Workload: In this study, author Nick Robinson discusses various jurimetrics dealing with workload like case admission rate, disposal rate, and pendency. He performed the analysis not only over all the SC cases together but also performed a comparative analysis across cases of multiple types like Appeals, Writ, Review, Contempt etc., for a comprehensive take on what is contributing to the workload.
Jurimetric studies that evaluate the implementation of laws
Evaluating the implementation of laws is to measure the use and misuse of the law, the time taken to dispose of cases registered under law and several such indicators. These help in understanding bottlenecks in the process of adjudication and suggesting legal reforms. Granular datasets on the adjudication of laws help in assessing the implementation of laws. A few such datasets and studies are presented below:
CivicDataLab and HAQ Centre for Child Rights prepared a dataset on POCSO Act. This dataset has granular details on POCSO cases adjudicated by the district courts in Delhi, Assam and Haryana. Indicators like time taken for case disposal, conviction rate, and number of hearings can be calculated from such datasets.
Habeas Corpus Petitions in the SC: In this study, the author used the dataset on preventive detention cases to analyse how the SC dealt with Habeas Corpus petitions. Jurimetrics like total time spent between the date of the detention order and the date of final disposal, and time spent in actual detention before final disposal by the Supreme Court were developed to analyse the implementation of the Habeas corpus writ in India.
Sunshine in the Courts: In this study, VIDHI developed novel jurimetrics like Legality Index, Convenience Index, Practice Index and Disclosures index to assess the implementation of the Right to Information (RTI) Act in Indian High Courts.
Jurimetric studies on human resources in the judiciary
In an ideal scenario, justice served should not depend on who the judge is. However, the background and profile of judges is an important variable in studying justice delivery. Datasets on judge's profiles help in measuring these indicators. JusticeHub hosts the following datasets and studies on this theme:
Know Your High Court Judges (KHOJ): KHOJ is one such dataset which has information on 1700+ High court Judges. This can help in measuring jurimetrics like the diversity of courts, vacancy in courts etc.
Background of Indian Supreme Court Judges: Prof Rangin Pallav Tripathy developed this dataset on the background of SC judges in India. It helps in measuring the representativeness, diversity and expertise of the Indian apex court.
Jobs for Justice(s) - Corruption in the Supreme Court of India: Using data on judgments delivered by judges and post-retirement appointments of judges, Madhav S Aney et al., analysed how judges rule in favour of the government in the hope of receiving jobs after retirement.
Jurimetric studies through Quantitative linguistics
When the judgement text is available, keyword searches and other Natural Language Processing (NLP) processes could be run on it to qualitatively analyse judgments and statutes. For instance, Enfold Proactive Health Trust identified “romantic cases” i.e. the use of POCSO Act to regulate and criminalise adolescents in non-exploitative consensual relationships. For this, the judicial text was used to classify a POCSO case as a romantic case.
JusticeHub’s current work on creating a Child Rights Data System is another such effort. In collaboration with Enfold, we are performing quantitative linguistics on judgments on the Child and Adolescent Labour Prohibition Act (CALPRA), Prevention of Child Marriage Act (PCMA) and Juvenile Justice Act. Datasets produced from such quantitative linguistic methods will help in doing a qualitative analysis of these acts and advocating policy reforms. You can read more about our work here: Link
All the above metrics and more are used to gain a comprehensive understanding of the functioning of the legal system. They allow for comparisons across different courts, jurisdictions, or time periods to identify patterns, trends, and areas requiring attention. And open data is key for the calculation of these indicators. As more datasets are created in the law and justice field, especially at the subordinate court level, more indicators could be developed to better assess the judicial system.
New Chief Justices of High Courts
Last Wednesday, the Supreme Court Collegium consisting of Chief Justice Chandrachud, Justice Kaul and Justice Khanna recommended the appointment of seven judges of High Courts as Chief Justices of various High Courts in the Country.
Justice Sunita Agarwal who hails from the Allahabad High Court is recommended to be appointed as the Chief Justice of Gujarat High Court. If appointed, she would be the only female judge to occupy the office of Chief Justice of the High Court in the current lot.
It is interesting to note that all the seven recommended appointees currently serve as the senior-most puisne judge in their respective parent High Courts. All of them have prior litigation experience and come from the Bar, rather than from the lower judiciary. Four of the recommended appointees (Justices Subhasis Talapatra, Siddharth Mridul, Dhiraj Singh Thakur, and Alok Aradhe) were designated as Senior Counsels before their elevation to the High Court and at least four of them (Justices A. J. Desai, Subhasis Talapatra, Dhiraj Singh Thakur, Alok Aradhe) served as standing counsel for Government/PSU/Statutory bodies.
To know more about the recommended appointees or other High Court Judges, refer to the Know Your High Court Judges (KHOJ) dataset available on Justice Hub. KHOJ dataset includes data of more than 1700 judges appointed between 1993 (after the creation of the collegium) and 2021. The dataset captures information across 43 variables including the personal, educational and professional background of India’s High Court judges.
Activities at the JusticeHub
New datasets on JusticeHub!
The Justice Hub now hosts the dataset related to cases disposed off by the Chief Commissioner of Persons with Disabilities (CCPD) in 2022. The data was manually curated by PACTA from the orders of CCPD. Researchers can use this dataset to analyse the state-wise distribution of the complaints, the profile of complainants, the average duration for disposal of complaints, the disability types, the status of benchmark disability, the subject matter and the issues within the subject matter present in the cases and if the remedy was given. The research report which brings out the insights from the analysis of the data can be accessed here
We also added a dataset related to the children adoption statistics in India. This data is curated from the adoption statistics of the Central Adoption Resources Authority (CARA). The dataset provides gender and state-wise adoption statistics from 2013 to 2022.
The dataset related to victim compensation from 2016 to 2022 was also added this month. This data was curated from the victim compensation scheme reports published by the National Legal Services Authority. This dataset provides information as to the amount of victim compensation awarded by respective State Legal Services Authorities in a particular financial year and the disposal pattern of the victim compensation applications. Researchers can use this data to examine how many victim compensation applications are received by legal services institutions every year, the percentage of disposal and pendency of applications, and the average amount of compensation awarded by State Legal Services Authorities (year-wise and state-wise) etc.
We also have a dataset of statistics on Indians in foreign prisons. The dataset, curated from one of the replies in the Question Hour Session in the Loksabha, contains the country-wise number of Indians imprisoned (including the undertrials) in foreign prisons.
JusticeHub at PyCon?
This month, we submitted a proposal at PyCon India 2023. We’d be talking about our work on deploying Natural Language Processing (NLP) methods on Indian court judgments to create structured datasets. These datasets help us analyse the working of the judiciary and the effectiveness of law. If you want to hear more about our work, please vote for our submission here: Datafication of Indian Court Judgments using NLP
We are planning to resume our “Date with Data” series on Justice Hub. These are webinars that we conduct with people who actively work on legal and judicial data and do a deep dive on one of such datasets - develop more jurimetrics. Please reach out to us if you have any interesting data stories to share, for a date :)