Integration challenges, immigrant characteristics and career satisfaction for immigrants in the field of accounting and finance: An empirical evidence from Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although immigrants are subject to structural and cultural vulnerability, little attention has been devoted to understanding the integration challenges they face in building a career in accounting and finance. This study investigates those challenges and addresses how such challenges and immigrant characteristics influence career satisfaction. The study draws on the life course perspective to survey Canadian immigrants. It finds that the integration challenges are multidimensional, comprising workplace discrimination, non-recognition of foreign education and experience, and ethnic differences, where the devaluation of prior education and experience is the worst challenge for new Canadian immigrants. Further, workplace discrimination and devalued education and experience negatively influence career satisfaction. However, ethnic differences exert no significant effect on career satisfaction. Evidently, this study is the first to measure dimensions of immigrant integration challenges and how they relate to career satisfaction. The identified challenges and suggestions may be of benefit to enterprises, government institutions, and professional bodies that aim to improve inclusion, equity, and career outcomes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it