Student voices within Indigenous social work practicum recommendations and the Seven Grandfather Teachings
Bibliographic record
Abstract
This article examines the integration of Indigenous perspectives, particularly the Seven Grandfather Teachings, in Indigenous social work education and field practicum, focusing on student experiences. Colonization has had significant impacts on Indigenous communities, leading to intergenerational trauma, which calls for the need for culturally appropriate social services. Historically, mainstream social work has been complicit in the oppression and genocide of Indigenous peoples, leading to negative perceptions among Indigenous communities. Western theoretical hegemony in education has marginalized Indigenous perspectives, emphasizing the need for inclusivity. Indigenous social work, rooted in acknowledging colonialism and oppression, promotes self-determination and cultural revitalization, highlighting the importance of Indigenization in the profession. Field education is emphasized as crucial for students, encouraging self-reflection and cultural sensitivity. The Seven Grandfather Teachings—love, respect, bravery, honesty, humility, wisdom, and truth—are introduced as guiding principles in ethical behaviour and relationships. The integration of these teachings into coursework and practicum experiences is highlighted, aiming to prepare students for culturally responsive social work practice. Student narratives are utilized to illustrate personal experiences and the application of the teachings in real-world settings. Overall, the article underscores the importance of cultural competency, self-reflection, and community engagement in addressing the unique needs of Indigenous peoples in social work practice.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".