Between diversity and meritocracy: employer and skilled immigrant perspectives from the Canadian context
Bibliographic record
Abstract
Purpose This study aims to empirically investigate and extend the diversity-meritocracy paradox outlined by Konrad et al. (2021) using skilled immigrants in Canada as a case study. Despite their significance in knowledge-based economies, immigrant voices are often marginalized in diversity, equity and inclusion (DEI) literature and management research. By focusing on skilled immigrants, who embody both diversity and meritocratic principles, this research addresses this gap. Through semi-structured interviews, we examine whether diversity and meritocracy are perceived as contradictory or complementary for skilled immigrants. Our findings not only contribute to theoretical understanding but also offer practical insights into the complexities of diversity and meritocracy in contemporary organizations. Design/methodology/approach This study utilizes qualitative, semi-structured, interviews and focus groups to gather data from both employers and skilled immigrants. Thematic analysis, guided by Braun and Clarke (2006), is employed to analyze the data. Participants include skilled immigrants and human resource (HR) professionals/managers. Data are collected through interviews and focus groups conducted between December 2018 and February 2020 in person and via video-conferencing. Findings This study unveils a discrepancy in perceptions between employers and skilled immigrants on DEI in Canada’s labor market. While employers prioritize meritocracy, emphasizing Canadian qualifications and experience, immigrants feel undervalued, encountering barriers due to cultural differences. Employers focus on past work experience over credentials, using behavioral interviews and proficiency tests for assessment. However, immigrants often perceive the selection process as opaque, and encounter explicit preferences for Canadian education and experience, which they view as discriminatory. Challenges in onboarding, training and workplace culture further exacerbate their experiences. These findings highlight the nuanced dynamics between meritocracy and diversity, underscoring the need for systemic change. Originality/value Despite employers’ claims of valuing diversity, our findings reveal a preference for “Canadian-ness” over immigrants' international expertise, perpetuating systemic barriers. Employers prioritize meritocracy but often conflate it with cultural conformity, hindering immigrant integration. Our analysis underscores the disconnection between organizational rhetoric and practices, urging a reconceptualization of diversity and inclusion policies. To foster truly inclusive workplaces, both surface-level and deep-level diversity must be considered. Policy interventions and enhanced intercultural competence are essential for leveraging the talents of skilled immigrants and promoting equitable employment practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.034 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.008 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".