Uncertainty and Colombian Immigrants' Encounters with the Foreign Credential Assessment System in London, Ontario
Bibliographic record
Abstract
My research examines the experiences of Colombian immigrants, who have settled in London, Ontario, in negotiating professional qualifications and aspirations in Canada, as well as the subsequent impact to their family unit’s spatial integration and their individual identities. The study specifically assesses how educated Colombian immigrants were able to attain the accreditation necessary for employment in their professions and what were their experiences in doing so? Participants’ journeys demonstrate a gap in cultural education in workplace practice and reveal a need to attend to the relationship between local contexts, professional identities, and workplace ethics to ameliorate the issues in accreditation that plague the Ontarian socio-economy. Participants and their families demonstrate diverse capacities to cope with the demands and adverse effects of accreditation. Participants confront challenges with steadfast determination and tenaciously seize every opportunity available to them. The testimonies of participants are of undeniable value to shape the approach to immigration policy and program development. To construct a comprehensive story of credentialing and capture the diverse narratives of Colombian immigrants, participants partook in either or both the focus group and semi-structured interviews, which proved fruitful methods for the sharing of stories. In the end, I successfully gathered 15 participants for 2 focus groups. My study sought to share knowledge among and with participants with an overarching goal of returning some of the autonomy that has been eroded by participants’ credentialing experiences in Canada. Participants generously shared their experiences.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".