“I am white female and that’s at the bottom of the barrel”: Sex educators’ sensemaking of whiteness for decolonial education
Bibliographic record
Abstract
In this arts-informed inquiry, I conduct a fine-grained analysis of sex educators’ embodied experiences of their white race in relation to anti-oppressive education. Working relationality with Kumashiro’s notion of ‘learning through crisis,’ I query how sex educators sense-make their whiteness with a specific focus on the ongoing colonization of Indigenous people in Canada. Drawing on a subset of data from a sensory ethnographic study, I interpret two key embodied experiences of crisis that caused the educators to experience racial paradox, impartiality, uncertainty, and discomfort in ways that informed the development of anti-racist/decolonial personal pedagogies and practices. Pushing back against settler-colonial favourings of a central, singular argument, I story and interpret the educators’ sense-making in ways that process the questions: what else, how else, and where else? As such, I strive to conduct this inquiry in ways that position whiteness interconnectedly rather than (re)centrally in decolonial and anti-racist sex education efforts.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.035 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.005 |
| 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".