Closing the gap: reflections on school social work and decolonizing practice
Bibliographic record
Abstract
This report explores the role social workers can play in closing the Aboriginal education and achievement gap in Canada.Aboriginal students in Canada receive less funding and are less likely to be successful in school when compared to non-Aboriginal Canadians (McMahon, 2014).As a result, Aboriginal students graduate at a much lower rate than non-Aboriginal students.The lower graduation rate experienced by Aboriginal students is often referred to as the Aboriginal education and achievement gap.Aboriginal students who are at risk of not graduating face a number of environmental barriers that make it difficult for them to be successful in the classroom.Therefore, support services, including social workers are integral to the success of Aboriginal students within the school system (Joseph, Slovak, & Broussard, 2010).This report outlines my practicum experience with the Aboriginal Social Work Program of School District 57 in Prince George, British Columbia and highlights the importance of culturally safe social work support in schools.Included in this document is a detailed description of Aboriginal social work and reflections on the importance of decolonizing our practice as social workers.This report is a synthesis of deliberative reflections, participation, and research that highlights handson learning in school social work.
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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 | 0.025 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.033 | 0.064 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.009 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 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".