Breaking the silence of racism injuries: a community-driven study
Bibliographic record
Abstract
Purpose Injuries resulting from racism are largely hidden by silence. Community services to provide healing from racism are missing in at least one Canadian city. The purpose of this paper is to identify the injuries suffered by immigrants who experienced racism and discuss the development of culturally appropriate programs and tools to address injuries from racism. Design/methodology/approach Participants representing visible minorities service providers from non-profit, public-funded organizations in a major Canadian city took part in two focus groups. Data from focus groups were thematically analyzed. Findings Racism produces traumatic and persistent psychological, social and intergenerational injuries. An ostensible gap exists in services, professional education and skills to address the psycho-social effects of this complex problem. The complicity of silence in both dominant and subordinated groups contributes to its perpetuation. A dearth of screening and assessment instruments is a barrier in identifying individuals whose mental health and addiction problems may have underlying racism-related etiology. Creation of community healing circles is recommended as a preferred method over individual “treatment” to expose and deconstruct racism, strengthen ethnic identity and intergenerational healing. Research limitations/implications These qualitative findings were generated based on the perspectives of a small purposive sample (n=8) of immigrant service providers and immigrants from one Canadian city. Many of these findings are consistent with the existing literature on internalized racism and racism injuries. Generalizability to the wider population of the province and of Canada requires further research. Practical implications Practitioners in health and social care as well as educators need to understand the injuries and internalized effects of racism to provide appropriate services and leadership. Development of anti-racism professional knowledge and skills, healing circles, and assessment instruments will contribute to deconstructing racism and mitigating its injuries. Originality/value Community-driven studies exploring racism and the lack of services to address the issue are scarce. This study pulls together the experience of service providers and their insights on ways to break the detrimental silence surrounding racism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".