Resources for
Anti-Racist Research
Anti-racist research intends to understand, challenge, and change the values, beliefs, and actions that sustain systemic racism. Please refer to this library for trainings, readings, and tools curated for an ICES audience to support implementation of the Guidance Document and Framework for Anti-Racist Approaches to Research and Analytics at ICES.
A Closer Look at Anti-Racist Research
This two-page document concisely summarizes key recommended actions at each stage of your ICES project.
Trainings
In this 20-minute video, Dr. Kimberlé Crenshaw introduces intersectionality. This frame and name describes how multiple “intersecting” forms of oppression create compounding experiences of marginalization.
In this 5-minute video, Dr. Stephanie Nixon explains how social structures produce both unearned advantage and disadvantage. To practice critical allyship, researchers should seek to understand their complicity in systems of inequality and work in solidarity with communities to dismantle these.
In this 6-minute podcast and article from the NEJM, Dr. Joseph Graves Jr. debunks common medical myths about socially defined races and diseases. Analyses of human variation have demonstrated that modern humans are not classifiable into biological races.
This article describes concrete examples of how structural racism is embedded in health research processes and suggests corrections. Researchers should name racism as the central concept that race data attempts to measure.
This 90-minute webinar thoroughly debunks “race science” and describes “race” as a social construct. Analyses of human variation have demonstrated that modern humans are not classifiable into biological races.
This 30-minute podcast and article describes critical race theory as a key underpinning of anti-racist practice:
- Recognize race as a social construct
- Centre in the margins
- Reporting inequities is not sufficient; include nuanced interpretation and plan for action
This 90-minute webinar provides advice and cautions for data collection, analysis, and reporting. Meaningful community engagement is essential when working with data from Black communities.
This article challenges the status-quo practice of considering race a non-modifiable risk factor for illness. Researchers should instead examine discrimination as a modifiable risk factor.
In this 45-minute podcast, LLana James discusses the influence of racism on medical practice and data. Listen from 31:42 – 41:45 for a focused conversation on racial biases in datasets.
This article describes errors in statistical reasoning that led to race-based treatment of hypertension and congestive heart failure. In a racially stratified society, race and racism are correlated with virtually all social interactions and economic options: there are cases where no adjustment is plausibly adequate to draw causal inferences from existing data.
This call to action recommends the systematic collection (and appropriate use) of race data. It notes priority areas for race-disaggregated reporting, the importance of authentic and sustained community engagement, and the urgent need for community data governance.
Tools for using ICES race and related data
This inventory of the existing race-related variables and their source is updated annually.
This Guide from BC Data Services intends to support users who work with existing Canadian administrative and survey datasets with race and related variables, such as census data and the Canadian Community Health Survey. It provides 9 recommendations brought to life with 14 illustrative case studies. It also includes a self-assessment checklist to help users assess their adherence to the recommendations.
Harm arises from both the non-use and problematic use of race and related data. Requirements are proposed to support the goal of appropriate use of these data to promote health equity.
Tools for planning appropriate methods
Scientists and project teams are encouraged to engage communities in the research process in a meaningful and respectful way to collaborate on how the research is framed and how data are used, interpreted, and shared.
Outlines practice standards for selecting research questions, planning engagements, hiring, analyzing results, and reporting results. Click “Log in as Guest” to access accompanying self-reflection exercises.
Scientists and project teams are encouraged to collaborate across disciplines to gain expertise from qualitative research, social epidemiology, sociology, political science, and related disciplines to contextualize studies that use race and related data.
These case studies showcase examples of how qualitative social science approaches can contribute to equity-focused research.
Tools for analysis and interpretation
Presents evidence for and recommendations to model (a) Racism as a fundamental cause of racial differences in socioeconomic status (SES); (b) SES as a fundamental cause of inequalities in health and mortality; and (c) racism as a fundamental cause of racial differences in health and mortality independent of SES.
Over-adjustment of covariates is common and may mask part of an exposure’s effect on an outcome. A systematically-constructed DAG may assist with identification of confounders, mediators, and colliders to inform appropriate adjustment strategies.
Provides recommendations for constructing causal diagrams that model race as a social variable (and provides examples of same).
Outlines a framework for incorporating equity concerns into causal decomposition analysis. Provides specific guidance (with examples) of where it is and isn’t appropriate to adjust for covariates.
Describes 7 steps that researchers should take to conduct intersectional research with quantitative data.
Tools for communicating results
CMAJ describes 10 practices authors must adhere to when preparing papers for submission and further suggests additional best practices for precise and respectful language to describe communities, considerations for the interpretation section, and considerations for community co-authorship.
Notes common missteps in the presentation and interpretation of findings in racial disparity research and makes recommendations for improvement, including explaining decisions to aggregate or disaggregate demographic categories, noting limitations of the groupings used, and discussing sources of missing data.
Search-optimized web glossary of fundamental equity-related terms.
Provides examples of person-first language and other non-stigmatizing language considerations.
Provides tips and examples for using active voice, present tense, chunking, and other principles of plain language communication.
Exemplar papers from ICES scientists
- COVID-19 in immigrants, refugees and other newcomers in Ontario: characteristics of those tested and those confirmed positive, as of June 13, 2020
- One size does not fit all: diabetes prevalence among immigrants of the South Asian diaspora
- Prostate cancer incidence among immigrant men in Ontario, Canada: a population-based retrospective cohort study
- Sex ratios at birth after induced abortion
- Sex ratios at birth among second-generation mothers of South Asian ethnicity in Ontario, Canada: a retrospective population-based cohort study
- Stroke disparities research: learning from the past, planning for the future
- Using knowledge exchange to build and sustain community support to reduce cancer screening inequities
- Using self-reported data on the social determinants of health in primary care to identify cancer screening disparities: opportunities and challenges
Get in Touch
"*" indicates required fields