The Wretched of the Work: Anger, Fear, and Hopelessness as Impacts of Experiencing Workplace Racism in British Columbia, Canada
Bibliographic record
Abstract
Drawing inspiration from Frantz Fanon’s work on the colonization of racialized subjects, this article illuminates how racial discrimination impacted the wretched of the work, in reference to a group of racialized civil servants, in primarily White institutions of public service in British Columbia, Canada. Specifically, using data from twenty-five in-depth qualitative interviews, the article presents findings on the affective impacts of workplace racism on this group of participants. In this regard, anger is discussed as internalized, nonviolent and pent-up frustration over oppressive everyday microprocesses that presented significant workplace barriers to racialized workers. Subsequently, fear is outlined as shaped by the lingering concerns on the part of racialized subjects over the very real prospects that their employers could retaliate against participants using any pretext and at any given time. Lastly, hopelessness is explicated as the feeling of disempowerment driven by the belief that workplace inequities would persist irrespective of what participants did to seek equal and respectful treatment at work. Ultimately, through outlining findings as anger, fear, and hopelessness, this article adds to the existing body of scholarship on how workplace racism not only leaves an indelible mark on racialized targets but also why it wreaks havoc in employment relations, further reinforcing existing empirical literature on the debilitating impacts of workplace racism. Lastly, in view of the fact that racialized public servants have received scant research attention, the findings underscore the need for publicly-funded employers to address White supremacy and institutional domination in their midst on a priority basis.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.040 | 0.011 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".