Bibliographic record
Abstract
This critical reflection is based on my practice encounter as a white settler social worker within the context of Child Welfare, in rural Canada during the late 1990s. This paper is in line with Karen Healy’s (2001) notion of critical social work, as a means to enhance systemic and related child welfare social worker practice. More specifically this paper addresses, through a specific case encounter with an Indigenous mother, how white settler social workers are systemically entangled in perpetuating acts of oppression. This critical reflection enables the reader to become aware of how mainstream social work practice, has the ability to unintentionally harm those service receivers that it actually intends to help. This paper critically addresses discourse around professional innocence, the risks of professional knowledge, representational violence and ethical practice dilemmas, within the context of a disguised practice encounter. The relevance of this critical reflection may be seen as a social justice initiative, catered predominantly towards white settler front line practitioners. These challenges are originating from within our own practices. Our practices are historically embedded in systemic colonial forms of discrimination and racism against First Nations, Métis and Inuit communities. I bring light to how white settler social workers should confront their own personal and professional pre-conceived notions, biases, and misconceptions and instead, implement anti-racist and anti-discriminatory practices within their work. This process begins with critical self-reflection.
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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 | 0.040 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.021 | 0.061 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.008 | 0.014 |
| 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".