Self-initiated international career transition: a qualitative case study of Pakistani immigrants to Canada
Bibliographic record
Abstract
Purpose The purpose of this study is to examine the career transition experiences of three immigrants from Pakistan in Canadian organisations using Nicholson’s four-phase transition cycle. Design/methodology/approach A case study approach was used, and data were collected through three in-depth, semi-structured interviews to determine how immigrants experience career transitions in Canadian organisations. Findings The findings show that all three participants had almost the same level of expectations before coming to Canada; however, there were significant differences in their career transition experiences. These findings demonstrate that immigrants’ career experiences can be understood and examined through the lens of Nicholson’s transition framework; their expectations and experiences at one stage subsequently affected their experiences at later stages. Research limitations/implications A longitudinal research design would be an excellent approach to explore immigrants’ career transition over time. Practical implications Organisations hiring skilled immigrants need to be more supportive of their efforts in reducing immigrants’ feeling of underemployment and discrimination. Originality/value The study contributes to the immigrant literature by presenting a new way of looking at immigrants’ experiences in Canadian organisations. It also contributes to the career literature by extending the application of Nicholson transition cycle to an underrepresented population (i.e. immigrants) in careers research.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.033 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 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".