Analysis on health status as well as living and job satisfaction of Chinese immigrants in Canada
Bibliographic record
Abstract
Objective To understand how Chinese immigrants evaluate their health status and how they are satisfied with the living and job situation in Canada.Methods A stratified sampling design was used according to the age of the participants.A semi-structured questionnaire was distributed to the participants for their responses.All data were entered into a pre-tested MS-ACCESS database,which was later converted into SAS format for analysis.Results The main problems raised by participants were low satisfaction to the health and living status;difficulties in finding suitable jobs,language barrier.The leading reasons for difficulties and dissatisfied things living in Canada were cannot finding a suitable job(45.0%),boing life(33.2%),language barrier(26.0%),hard to make friends(23.5%).Conclusion The results from this study are expected to have important implications in terms of how best utilizing the human resources in the Chinese population in Canada.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".