“Strangers in the new homeland”: the personal stories of Jamaican Canadian adults who \nmigrated to Canada as children
Bibliographic record
Abstract
Globalization has and continues to impact developing countries such as Jamaica, a nation that depends on countries such as Canada for economic support. Within this structure and dependence is migration, which is a common practice in Caribbean countries. Given the power structures involved in the global economies, where developing countries such as Jamaica experience economic hardships, parents of the participants in the study made the tough decisions to migrate to Canada to make a living and support their families. In the process of migration, children (participants) are often left behind with the plan to be reunited with their parents in Canada. It is argued that the process of reunification between children and their parents is oftentimes characterized by many problems, misunderstandings, unaligned expectations, resulting in unanticipated tension and conflictual relations between children and parents. This study presents qualitative research findings that highlight the social and economic barriers that Jamaican Canadian adults experienced when they reunited with their parents in Canada. Results from the study revealed that the participants experienced isolation, devaluation of their education, and anti-Black racism, yet they were able to persevere as successful individuals who continue to contribute to the development of Canada. Using a Critical Race Theory (CRT) framework to understand the stories of the participants, findings revealed that anti-black racism and discrimination targeting Black people in their migration, during integration, and settlement stories in Canada are not aberrant but consistent with the anti-black racist migration history of Canada. If anything, participants’ stories reveal how little has changed in the struggles of Black people to migrate, integrate, and settle in Canadian society. The outcome of this research adds to the ongoing dialogue with service providers, learning institutions, policy makers and the general Canadian population about the importance \nof addressing racism and discrimination targeting immigrants of colour in Canada, as well as to improve on how social services are provided for immigrants of colour in Canada.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.038 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".