Sierra Leone newcomers in Winnipeg: their experiences with seeking help
Bibliographic record
Abstract
African refugees and immigrants are arriving in Manitoba in vastly increasing numbers and a review of the literature indicates that they are experiencing barriers to successful integration. The goals of this research are to understand the experiences of Sierra Leonean newcomers with seeking support and identify specific needs and services that might be helpful. Using qualitative methods, interviews were conducted with Sierra Leonean newcomers. The analysis of the data indicates that newcomers want financial independence and to fit into Canadian life. The process to get their foreign credentials accredited is difficult and affects their ability to gain economic security. They rely on informal networks with other Sierra Leoneans for assistance to acquire resources when they are unable to get help from service providers. As well, newcomers are concerned about their community image, feelings of isolation and sacrificing all of their dreams. Recommendations from this study include the need to recognize and support African community leaders in connecting with newcomers to share accurate and vital information. In addition, services for employment and the accreditation of foreign credentials should be appropriate, affordable and timely. Changes to policies and to the provision of settlement services are necessary to improve the accessibility and availability of resources required for the successful integration of African newcomers.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".