Bibliographic record
Abstract
Despite its prefix, the lasting impact microaggressive behaviour has on racialized people is no small thing. This thesis investigates microaggression as a cultural phenomenon, providing new insights on the connection between covert racism, socialization, and workplace culture. Postracial beliefs favour the idea that society has overcome or is beyond racism, that racist behaviour is the exception not the rule. As postracialism interacts with Canada’s national image, it further obscures damaging ideologies affecting how we understand professional culture and ways to make more inclusive workplaces. Semi-structured interviews were conducted with racialized employees to gather first-hand accounts of the barriers to the integration of equity, diversity, and inclusion (EDI) in the professional landscape of the Greater Toronto Area. Thematic and framing analysis lend themselves to the analysis, identifying solutions and strategies to cope with and mitigate microaggression at work through three frames: racialization, meritocracy, and professionalism. Keywords: critical race theory, microaggression, equity, anti-racism, black Canadian studies, professionalism and labour
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.056 | 0.032 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".