Perceptions of Black Immigrant Workers Regarding Workplace Diversity in Calgary, Alberta, Canada
Bibliographic record
Abstract
Globalization has resulted in permeable boundaries resulting in a highly mobile labor force. Canada's multicultural environment and its Federal Skilled Worker's Policy, renamed the Express Entry Program, attract many immigrants seeking employment opportunities comparable to their qualifications and work experience. Instead of equality and advancement, black immigrants are often underpaid and face few opportunities for advancement. Research has indicated that strong diversity policies and management are promising solutions to these issues. This qualitative study aimed to explore the perception of skilled Black immigrants' workplace experiences and diversity strategies to mitigate discriminatory practices. Johnson's polarity management, as adapted in Benet's polarity of democracy, was the conceptual framework that guided this study. Narrative inquiry elicited information through in-depth interviews of 10 purposively sampled Black immigrant participants who spent a minimum of five years in the workplace. Interview data were analyzed using qualitative data analysis software. Thematic analysis indicated that increased diversity was perceived as a solution to inequality. The participants' perceptions showed the prevalence of either/or thinking and views of diversity in isolation from the interdependent pole that forms the unique polarity of diversity/equality. The findings identified a perceived need for a paradigm shift from understanding diversity as a standalone concept to seeing these workplace issues as a polarity dilemma—to better balance the diversity/equality polarity. The shift in thinking could address the ubiquitous challenge of paradoxes in diversity outcomes, which may have a positive social change implication for increased diversity in policy formulation and implementation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".