RECKONING WITH OUR PRIVILEGES IN THE CYC CLASSROOM
Bibliographic record
Abstract
As three white educators working in three different post-secondary contexts, teaching child and youth care (CYC) to diverse undergraduate students, we are interested in exploring the ethical, political, and pedagogical challenges and opportunities of creating learning spaces that can support concrete actions towards decolonizing praxis, social justice, and collective ethics. In order to support each other’s developing praxis, we have recently begun meeting monthly to explore various questions and tensions that exist for us in this work. These meetings have been deeply generative for us in that they have produced a sense of solidary and accountability to each other and our developing pedagogies. This paper attempts to capture some of this experience by sharing three perspectives reflective of the challenges and successes each of us have experienced in our respective institutions.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.042 | 0.030 |
| Scholarly communication | 0.022 | 0.008 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.003 | 0.012 |
| 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".