Families Building Nations, or Nations Building on Families? An Exploration of How African Caribbean Immigrants (Re) Construct Family in the Context of Immigration and Oppression in Canada
Bibliographic record
Abstract
This study retrospectively explores the experiences of separation and reunification of African Caribbean immigrant families and how they rebuild their families in the context of immigration and oppression in Canada. Experiences of multiple separations and prolonged reunification have been expected and commonplace for many Caribbean families who have immigrated to Canada since the 1960s. There is a gap in social work knowledge about the experiences of African Caribbean immigrant families in Canada, and this lack is particularly important in light of the frequency of these families’ contact and conflict with institutions such as child welfare agencies, the educational system, and the criminal justice system; these are social institutions where social work has an instrumental role. The study sample consisted of 27 participants, including 25 who identified as African Caribbean women and men, and two who were not African Caribbean-identified. This qualitative study used a decolonizing critical constructionist grounded theory methodology, with data collected through semi-structured individual interviews and focus groups. The major themes that emerged from the study include “Cast Out,” “Keeping Up,” and “Child Rearing.” Together, these themes point to the specific realities and complexities involved in the impact of multiple separations and extended reunification on African Caribbean immigrant families. For social work, the findings offer important contextual knowledge about African Caribbean immigrant families that may help to inform transformative policies and practices. Additionally, the findings aim to contribute towards depathologizing and decolonizing understandings of the historical and contemporary social conditions and subsequent life choices and chances of African Caribbean immigrant families 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.037 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".