Experiences of Racism and Race-Based Traumatic Stress Symptoms Among People of Chinese heritage in Canada: The Moderating Role of Resilience
Bibliographic record
Abstract
People of Chinese heritage in Canada face historical and ongoing racism, which has been exacerbated since the onset of the COVID-19 pandemic. Theories suggest that experiences of racism may lead to race-based traumatic stress symptoms; however, this association has not been examined among Chinese people in Canada. Furthermore, most research has focused on the adverse effect of racism on poor mental health symptoms, little is known about protective factors in the link between racism and race-based traumatic stress symptoms. To this end, I aim to explore the protective role of resilience from both aspects of individual resilience (i.e., an individual’s characteristics that enable them to bounce back from adversities) and collective resilience (i.e., the availability of practical and emotional support from the community). The purpose of this thesis is to explore how resilience protects against the adverse effect of racism on race-based traumatic stress symptoms among people of Chinese heritage in Canada. A sample of 367 adults who self-identified as of Chinese heritage in Canada (e.g., 46.59% women; Mage = 33.9) completed self-report questionnaires. I adopted SPSS PROCESS Model 1 to examine the moderating effect of individual/collective resilience on the relationship between experienced racism and race-based traumatic stress symptoms. The results showed that more experiences of racism were significantly related to increased race-based traumatic stress symptoms. Collective resilience buffered the adverse effects of racism on race-based traumatic stress symptoms, while individual resilience did not moderate this association. These findings suggest that collective resilience, rather than individual resilience, mitigates the negative impacts of racism on race-based traumatic stress symptoms. This study highlights the necessity of recognizing the experiences of racism and its adverse impacts on the mental health of Chinese people in Canada. Furthermore, it underscores the importance of fostering collective resilience and community-based support systems among people of Chinese heritage in Canada.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".