An evaluation of the role of one community college in immigrant settlement
Bibliographic record
Abstract
This qualitative study examines the experiences of immigrant graduates from one community college in the areas of recognition of prior experience and credentials, admission, retention, graduate placement, and their perceptions regarding the value of the college experience in assisting them with settlement in Canada. Quantitative data were also collected relating to salary so that comparisons could be made with previous studies in this area. Sociological frameworks developed by Hardiman and Jackman (1996), Rawls (1971), and Mitchell and Shillington (2002) are drawn upon to direct the research and interpret the findings of this study with an emphasis on social justice. In addition, an expert panel was utilized to guide the refinement of the research questions, comment upon the findings and evaluate results. Interviews were conducted with thirty-seven participants to gain their observations and insights as to the role the college played in assisting them with settlement in Canada. The findings suggest that the college participating in this study has met or exceeded participants' expectations in the areas of overall college experience, searching for employment (time and type), potential for career advancement, and marketability of graduates. Further, the findings of this study indicate that the college has had a positive impact on both community participation and settlement as it relates specifically to employment. However, the findings also indicate that the college has done little to facilitate settlement in the community of those interviewed. Finally, not withstanding participants' reported successes in searching for employment, the relatively low wages, precarious nature of the work secured by those interviewed, and an overall deterioration in earnings calls into question employers' apparent willingness to operate in a manner which contributes to maintaining an environment of social and economic justice within Canada. Federal and provincial governments, social organizations and many employers have become aware of the multiple issues immigrants experience upon arrival in Canada. Indeed, many of these groups have begun to work together putting programs and services in place to help. This study contributes to gaining a better understanding of the challenges immigrants may face in the settlement process and offers recommendations to enhance one college's efforts in this area. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".