Bibliographic record
Abstract
In 2018, using in-depth, semi-structured, collaborative dialogues, I asked 11 child and youth care practitioners working in various Canadian provinces, including British Columbia, Alberta, and Ontario, “How do you understand, name, reproduce, contest, and struggle with White settler privilege?” The intent was to name and challenge the dominant Whitestream norms in child and youth care. This project was inspired by the significant work of Indigenous and racialized activist–scholars to address the ongoing overrepresentation of Indigenous families across colonial systems in which child and youth care practitioners work, such as the child welfare and justice systems, and the underrepresentation in others, such as educational systems. Participants named colonial violence and systemic racism as entrenched in child and youth care practice while recognizing the difficulty of challenging dominant White norms and conventions in the classroom and field. I explore how this key finding unsettles child and youth care pedagogy and practice. In closing, I propose two practical ethical pathways towards unsettling White settler privilege in child and youth care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.040 | 0.058 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".