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Data on detention: Using official data in qualitative research

Link to registration: https://forms.gle/dmk9aGpb2cnJKuZF6.

This workshop explores how to incorporate hard-to-access official data into qualitative research on law, governance, and public policy in Hong Kong. We will discuss our experience as researchers on the three-year RGC-funded project Immigration Detention and Vulnerable Migrants in Hong Kong: Evaluating the System, Facilitating Reform.

Official data from 2017 to 2019 shows that Hong Kong detains almost as many (and sometimes more) people each year for immigration control as the number of people imprisoned annually for committing crimes. Despite the large number of migrants routinely put behind bars, there is very limited official data on immigration detainees. Considering that detention concerns persons deprived of their freedom, the lack of data is markedly concerning. In contrast, the prison authority regularly publishes statistics on persons held in their institutions, including prison population numbers by gender, number of self-harm incidents, and cases of solitary confinement.

Our research team at the Faculty of Law, Chinese University of Hong Kong is conducting the first detailed study of immigration detention in Hong Kong. In addition to secondary literature review, analysis of government documents, and research interviews, we have been engaging in extensive data gathering.

In this workshop, we will discuss the landscape of open government data and challenges in accessing data. We will share our attempts in obtaining official data through access-to-information (ATI) requests via the Code on Access to Information, including specific examples of challenges we faced and how we navigated them.

With relevant data scattered across departments and source formats, cleaning and compiling data can be an arduous task. We will share how we have tackled cleaning messy data, aggregating data across many sources, and crucially, how to analyse and cross-reference your resulting dataset to ensure accuracy. We will also discuss our efforts to present and share this data in ways that facilitates practical impact.

This workshop would be of interesting to anyone interested in civic data and the challenges and process of data gathering. For researchers interested in filing their own ATI requests, please feel free to bring your draft questions for discussion.

About the data page: https://dsprojects.lib.cuhk.edu.hk/en/projects/immigration-detention-in-hong-kong/

For more information about the research project, please visit the project website: https://immigrationdetentionhk.net/


Date: 22 April 2022
Time: 1500 – 1700
Location: Online via Zoom
Language: English


About the Speakers:
Surabhi Chopra is an Associate Professor at the Faculty of Law, Chinese University of Hong Kong.  She researches the legal regulation of low-income migrants, national security laws, and sectarian violence.  Prior to joining academia, she trained as a barrister (Lincoln’s Inn 2006) and practiced law in the UK and India. She also has considerable experience advising governments, multilateral organisations and NGOs on human rights law and policy. She has a law degree from Cambridge University, an MSc in Human Rights from the London School of Economics, and a BA in Anthropology from Harvard University. 

Chloe Fung is a researcher with a background in geography and a particular interest in data analysis and visualisation to advance rights protection and transparency. Her interest in refugee issues and migrants’ rights began when studying refugee law in Amman, Jordan during her Arabic language studies. She has been a Legal Casework as well as Research and Policy Volunteer at Justice Centre Hong Kong. She conducted a comparative research project on East Asian refugee status determination procedures as well as detention, right to work, and resettlement in Hong Kong, South Korea, and Japan. She is an avid language learner and was selected as a Kathryn Davis Fellow for Peace in 2020 for foreign language training.

Date & Time
22 April 2022
Location
Online
Language
English