Maternal Health Care Challenges Within African Immigrant Communities
Bibliographic record
Abstract
Historically, immigration has had a significant impact on the changing demographic of the Canadian society. Each year more newcomers enter the country. There are more than 45 ethno-cultural associations and more than 100 different ethno-cultural groups residing in Nova Scotia. In the recent past, social science researchers are becoming increasingly involved in identifying ways of effectively addressing the social and health needs of this culturally diverse Canadian population. There is very limited literature on the Nova Scotian experiences of immigrant women especially those of African descent. For the government to develop public policy that ensures the inclusion of vulnerable and high-risk populations in our society such as recent immigrants and black people, their perspectives should be considered. Some steps are being taken by individual researchers to illuminate these perspectives. The paper will discuss the findings of a project that examined the health care experiences of immigrant women in a Canadian province with a goal of illuminating health care needs of recent immigrant women and facilitating community capacity building to create positive change for more accessible health care. The data collection method was primarily focused group meetings and workshops held with the individual immigrant communities. Although the project was conducted with immigrants from five regions of the world, this paper will focus on the experiences of first generation immigrant women of African descent with emphasis on their perspectives on the process mothering in a multicultural society. The paper will discuss their childrearing needs and their attempt to address these needs within the spaces of multiculturalism, the two predominant ones being the Canadian culture and that of their countries of origin. The paper will conclude with some suggestions for change at both the practitioner and policy level in order to effectively address the social and welfare needs of this population.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| 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".