Review Of The Job Search Workshop Program: Citizenship And Immigration Canada
Bibliographic record
Abstract
The objectives of this review of the Job Search Workshop Program (JSW) were to assess JSW as it is currently delivered across Ontario, and to make recommendations for improving the delivery of the program. JSW is an Ontario-wide program funded by Citizenship and Immigration Canada since 1997, and aims to help newcomers find jobs by orienting them to the Canadian labour market. For the review, RealWorld Systems collected information from many different perspectives, including the research literature, JSW agencies, clients, employment experts, and previous assessments of the program. The main findings were: JSW directly addresses the most important difficulty faced by immigrants to Canada, as well as one of the primary outcomes of Canada’s immigration policy – integration into the labour market. The JSW service model (providing workshops in independent job search techniques to newcomers) is supported by research and community needs. However, the current curriculum and activities focus on general orientation to the job market, which has limited effectiveness. JSW is provided by agencies across Ontario, providing a service infrastructure with many committed and skilled staff. JSW is not being defined or delivered consistently across the province, and staff qualifications and program activities vary widely. Performance data are not consistent with JSW’s goals, data collection is spotty and unreliable, and the quality of the data is not adequate for monitoring or improving the program. The report makes five recommendations for the improvement of the Job Search Workshop program.
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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 | 0.018 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.029 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".