Data Transparency in Anti-Asian Hate Crimes under COVID-19
While a number of Stop Asian Hate protests took place in North America in 2021, three of my classmates and I were interested in how the scholars, community leaders, and media gathered Anti-Asian Hate Crimes statistics, and whether the authorities have effectively leveraged the data to formulate strategies accordingly.
With the recommendation and supervision of Dr. Beth Coleman, we received a grant from the University of Toronto and University College London to conduct formal research on the topic. We interviewed experts from academia and community organizations to understand the existing data policies, and envision a solution roadmap to bridge the collaboration gap between various parties.
As we worked on our research paper, the COVID-19 pandemic is still developing, and so are the consequences of it in our society. Our study proposes a snapshot of anti-Asian sentiment that has risen along with the spread of the disease, especially focusing on a Canadian perspective.
Canada has a population of over 37 million people, of which 6 million are Asians (16%). Since the beginning of the COVID-19 pandemic, the Asian population has experienced a spike in hate crimes against them according to major news outlets:
The numbers shown in news outlets are alarming. However, there is a lack of transparency in how the data was collected and interpreted, which prevented us from grasping the totality of the Anti-Asian Hate Crimes situation.
We conducted 2 interviews with:
An Assistant Professor from the Department of Sociology at York University. Focused on data collection methods and collaboration between academia and community organizations.
A Project Lead at a leading community organization that supports Chinese Canadian communities. Focused on existing data policies and tackling online racism.
Our research report encompasses key insights from:
Official governmental report and studies
Media articles from news outlets
Our research reveals the Asian community lacks trust in authorities considering how the complicated legal and prosecution procedures potentially undermine the effectiveness of the reporting mechanism. A large number of unreported anti-Asian hate crime incidents remain invisible to the authorities. Also, there are inherent limitations in the types of data collected by the police departments, as the race variables of both victims and abusers are not recorded.
While the authorities, community organizations, and academic researchers intend to mitigate Anti-Asian Hate Crimes, there is a collaboration gap as each party collects and manages their own data without an effective communication mechanism. No one understands the complete picture, making it difficult to estimate the true extent of Anti-Asian Hate Crime in Canada.
Based on our findings, we proposed two solution frameworks to alleviate the challenges:
Collaborative Roadmap: Authorities, community organizations, and academic researchers ought to collect, clean, and analyze Anti-Asian Hate Crime data in a centralized manner, ensuring a consistent data management approach and boosting public confidence.
Online Hate Policies: Social media companies should review their existing protocols in reporting and removing hateful content, or create algorithms to manage their content automatically.