Carriers of Coloured Credentials: The Devaluation of foreign Credentials and its Impact on the Career Trajectories of Professional African Immigrant Women in the Canadian Labour Market
Bibliographic record
Abstract
This thesis examined how the devaluation of foreign credentials impacts the career trajectories of African immigrant women from professional backgrounds in the Canadian labour market. The participants were professional women from different African countries and various professional backgrounds, resident in four Canadian provinces. They arrived in Canada with qualifications and years of experience in six broad professional categories: law, medicine, nursing, teaching, accounting & finance, and administration & human resources (HR). The thesis sought to reveal the role of the devaluation of their foreign credentials in determining the trajectory of their careers and how they negotiated this barrier. Discourses of devaluation/non-recognition of the foreign credentials of new immigrants in Canada have gained currency over the years; however, the experiences of professional African immigrant women with credential devaluation and their negotiation strategies have not received enough attention considering the increasing numbers of Africans in Canada. Using a qualitative phenomenological approach, I examined their experiences in the light of the points system of immigration, which gives premium points to applicants with high levels of education and work experience. Data was collected through in-depth interviews from a sample of 22 participants. The findings revealed a disruption in the career trajectories of professional immigrant women; their experiences were incongruous with the expectations derived from the point system. They encountered formal and informal modes of credential devaluation in the Canadian labour market through lengthy and expensive recredentialling processes as well as an intangible demand for Canadian work experience. The experience of credential devaluation for African immigrant women was not a one-time issue, it had initial and enduring dimensions that extended into their experiences on the job after accessing their preferred occupations. The study also underscored the resilience and perseverance of African immigrant women in overcoming these devaluation barriers to forge ahead in their careers or chart new paths for themselves. Ultimately, these professional African immigrant women exercised agency in determining how to overcome systemic and institutionalized credential devaluation designed to lock immigrant women into low level, low paid jobs to rise into professional roles within the Canadian labour market.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".