Culturally responsive training: exploring grief, loss, and spirituality
Bibliographic record
Abstract
Eurocentric principles largely influence and impact the way service providers interact with and provide support to individuals of African Descent. There is a lack of culturally specific resources for African Canadians dealing with grief and loss, as well as a lack of exploration into the long-lasting effects when these communities are not supported by traditional healing methods. The researchers aim to answer the following question: what are the culturally specific issues when dealing with grief and loss in the context of African American and African Canadian cultures, and what role does spirituality play within this process? This research explores ways service providers can support African Canadians through grief and loss, with a specific focus on evaluating the Culturally Responsive Grief Training initiative developed by the Nova Scotia Association of Black Social Workers (ABSW). This project proved successful in delivering culturally responsive training to service providers and community members to help African Nova Scotian communities cope with individual, collective, and complicated grief. Suggestions for further research include an in-depth exploration of grief and loss from an Africentric worldview as it relates to African Canadian communities, as well as the development of more culturally specific services and interventions to support traditional healing methods.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".