Data use: Cultural safety and preventing community harm

Under the Anti-Racism Data Act (ARDA), identity data can be used by ministries for the purpose of identifying and eliminating systemic racism and advancing racial equity. This purpose can be achieved through different approaches, including:

 On this page

• Cultural safety in data use
• Mitigating community harm in data use
• Preventing community harm in reporting on data
• Related links 

Cultural safety in data use

Best practices include:

• Work in a distinctions-based way with Indigenous Peoples to support meaningful and effective participation in decision-making around data. If ministries have questions, reach out to the Declaration Act Secretariat at declarationactsecretariat@gov.bc.ca 
• Work in collaboration with racialized communities implicated in the work to understand needs and priorities in relation to their data 
• There are cultural, spiritual, religious and/or linguistic differences across each community. Recognize this diversity to avoid omitting certain identities in your analysis
• Understand community context by learning about the different histories, cultures, norms, meeting protocols and other customs of the groups you are working with:
  • Review available documents and understand any calls to action from the community
  • Communities are not homogenous. Different groups within the same community may have opposing views and it’s critical to examine whether work is inclusive of a diversity of identities in a specific community
• Take an intersectional approach and consider interactions between variables (for example, race and gender and income):
  • Intersectionality recognizes an individual may experience more than one form of discrimination and/or marginalization. An intersectional approach considers a person’s whole identity and helps reveal these layers 
  • Understanding how a person’s overlapping social identities relate to their experiences of systemic racism is key to finding solutions that work for everyone
  • Reflect on what identity characteristics may impact individuals' access to and experience with your program, policy or service. Failure to collect data about relevant identity characteristics may lead to important perspectives not being considered in provincial programs or policies. At the same time, collecting data that cannot be meaningfully used is unethical

Avoid:

• Using Indigenous and racial identity data without a clear benefit to community 
• Ignoring or overlooking the specific historical context of Indigenous Peoples and racialized communities 
• Over-simplifying analysis by ignoring how variables intersect or interact with each other

Mitigating community harm in data use

What to do:

• Ensure the use of data benefits the community it is about. For example, the data is used to address systemic root causes of racism and reduce barriers, rather than used as a means of control 
• Ask the community about their concerns about how data could be used
• When developing research questions and analysis, it should be understood and agreed upon that the Indigenous and racial identity categories being measured are socially constructed rather than biologically defined 
• Consider a range of explanatory factors for inequities, including historical and/or current social structures (policies, practices, actions)
• Include and centre the perspectives and knowledge of racialized and Indigenous people 
• After doing your own research, ask the community if there is additional context or other information the researchers need to know to properly understand the data the way the community understands the data and to accurately reflect their experiences
• When proposing solutions, focus on the social and/or systemic conditions that need fixing rather than on the behaviour of individuals
• Assume that inequities are the result of systemic issues rather than inherent characteristics of individuals or communities (for example, genetics) 
• Be aware that cognitive biases such as confirmation bias can impact the interpretation of the data. Take time to consider how your own position, biases and assumptions may impact the way you interpret the data and be mindful of potential biases during the community harms review of the analysis  
• Equip yourself with tools to address unconscious bias: 
  • Take the GBA+ and the Policy Process eLearning course with special attention to the “Recognizing and mitigating our biases” section 
  • Review the “Unconscious biases” section of the GBA+ Policy and Legislation Workbook (PDF) and the Quick tips: Reducing bias in decision making (PDF) resource from the British Columbia Ombudsperson
• Conduct, record and update risk assessments regularly across all stages of the data cycle:
  • Ministries should review the Core Policy and Procedures Manual Chapter 14: Risk Management, which presents the B.C. government's risk management policy for an integrated enterprise-wide risk management process. The B.C. government’s Chief Risk Office provides guidelines for risk management
  • Contact data-act@gov.bc.ca for questions about risk assessment and assistance in applying risk guidelines to data projects 

Preventing community harm in reporting on data 

What to do:

• Provide context and interpretation for the data, including a range of explanatory factors for any inequities, to avoid having the audience come to harmful conclusions and/or further entrenching stereotypes 
• Uphold commitments around reporting with respectful communication to the impacted community
• Sharing research with the impacted community prior to publication provides an opportunity to prepare for any attention, good or bad, they may receive as a result of the findings becoming public
• Share results in accessible formats, using plain and respectful language 
• Provide information on any limitation of the data or the findings 
• Use tools like the Accessibility and Inclusion Toolkit for accessible design
• Refer to the Citizen engagement highlights package for good public engagement practices
• Follow the Guide on Using Categorical Race & Ethnicity Variables (PDF) for research and reporting
• Pay attention to the positive concepts of well-being, thriving, hope, happiness and self-determination instead of solely focusing on the negative issues such as poverty or disease. This also means exploring if a strengths-based statistic could be reported instead of a deficit-based one (for example, use "80% were employed" rather than “20% were unemployed”) 
• Be aware that language may change over time and may not be the same in all contexts. Take steps to understand and keep up to date on these changes 
• Share how the data has worked toward a specific racial equity goal
• When considering reporting on data, ask whether doing so will support a specific racial equity goal or a community’s goals

Avoid:

• Using Indigenous and racial identity data solely for institutional reporting without action. To avoid unnecessary collection of data, consider how to support anti-racism actions prior to starting data collection 
• Assuming the interpretation of data is correct without validating with the communities represented 
• Reporting solely on race without contextualizing the systemic and compounding factors that racialized groups are subject to 
• Framing differences between communities in ways that pathologize, blame or stigmatize 
• Deficit narratives when reporting on conditions or outcomes for racial or Indigenous people. Instead:
  • Humanize data about racialized and Indigenous people through respectful terminology, intentional and careful language use
  • Discuss a range of explanatory factors for inequities, including historical and/or current social structures (policies, practices, actions)
  • Highlight the issues as systemic rather than individual. For example, say “the system is flawed and designed to favour people with advantaged backgrounds”, rather than “you/your community did not try hard enough.”