The enhanced mentoring program for skilled Korean immigrants: an effective tool for successful integration into the Canadian labour market? (A Grant Proposal)
Bibliographic record
Abstract
Koreans have immigrated to Canada in the last twenty years seeking a better quality of life. The vast majority of recent Korean immigrants have been accepted under the economic class category, which indicates that they have either human capital or financial capital. However, most Korean immigrants experience downward mobility and reside in an ethnic bubble. Furthermore, mainly low confidence in English communication and cultural differences have impeded the participation in multicultural settlement services. Even some of the existing employment programs offered by settlement service providers are not approachable due to the limitation of eligibility. This practical MRP attempts to find a pragmatic solution to address the skill under-utilization issues experienced by skilled Korean immigrants. A specialized mentoring program is examined as a support for skilled Korean immigrants. The program aims to give them access to the Canadian labour market by integrating multiple facets of settlement and employment services. Key words: Skilled Korean Immigrants; Mentoring Services for Skilled Immigrants; Internet Based Employment Services; Labour Market Integration; Grant Proposal
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.004 |
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".