Bibliographic record
Abstract
White supremacist ideology is the elephant in the social work classroom, negatively impacting educators’ abilities to facilitate discussion and learning. One of the most effective ways to dismantle and organize against white supremacy is to politicize the seemingly benign moments that occur in the classroom that can create discomfort for students and instructors. Politicization includes identifying and addressing both the racial (micro-) aggressions that occur in the classroom and the processes and institutional policies that create complacency and lull us to sleep. In this conceptual piece, we use a Critical Race Theory (CRT) framework to understand how white supremacy perpetuates itself in the classroom, with a particular focus on whiteness as property. As well, we explore what it means to decolonize the classroom. Using a vignette based on our teaching experiences, we use these two frameworks to analyze classroom dynamics and interactions, and discuss how implications for social work education include waking from the metaphorical sleep to recognize the pernicious effects of whiteness and white supremacy. Included are practical individual teaching, relational, and systemic suggestions to enact change.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".