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Dataset . 2022
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
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KHOJ - Dataset about the Indian High Court judges

Authors: Apoorv Anand; Rangin Pallav Tripathy;

KHOJ - Dataset about the Indian High Court judges

Abstract

The KHOJ (Know Your High Court Judges) dataset includes data on 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 backgrounds of India’s High Court judges. It opens pathways for researchers who are looking to probe deeper or wider into the composition of the High Courts and those who want to undertake jurimetrics studies which explore the linkage between judicial behaviour and the background of judges. The core philosophy behind building such a dataset is the realization that people of the country should have more information about judges whose decisions have a real impact on such people's lives. This dataset is the result of a joint effort over 15 months involving more than 30 students and 10 professionals who volunteered their time and efforts in preparing this dataset. This was a collaboration between NLUO’s Centre for Public Policy, Law and Good Governance, Agami and CivicDataLab. It started with the Summer of Data 2021 programme where students from across the country became the original data creators using official and publicly accessible data sources.

{"references": ["https://www.epw.in/journal/2022/42/law-and-society/glass-ceiling-high-courts.html", "https://www.indiaspend.com/data-gaps/few-women-many-lawyers-what-a-new-dataset-on-high-court-judges-reveals-835627"]}

More info here - https://justicehub.in/initiatives/khoj-india

Related Organizations
Keywords

high court, india, open data, judiciary, judicial accountability, judicial appointments, law, judges, justice

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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