Cripping sex education: reflections on a public pedagogy project
Bibliographic record
Abstract
In response to recent calls for ‘cripping sex education’, we describe and reflect on an 11-week public pedagogy project in Canada that paired five community sexuality educators with 78 undergraduate students to make digital sexuality education tools for disabled, Deaf, and queer children and youth. From a perspective that argues for a genealogy of crip desire in childhood, we reflect on the possibilities and limitations of an intellectual partnership project, called Cripping Sex Education: Creating Digital Tools for Disabled, Deaf, and Queer Kids. This public pedagogy project centred crip theory, coalition building, and critical digital pedagogy in its aim to discover how cripping sex education might be feasible within the parameters of our institutions, vocations and lives. The work required all partners to consider new pedagogical formations of sexuality education, including through ethical engagements, relational rights, and expansive approaches to access. Interviews with three student participants reveal that cripping sex education involves thinking broadly about accessibility, challenging normalcy and, as disability justice principles attest, centring those who are most impacted. We close with recommendations for future cripping sex education pedagogical work that honours already existent crip desires, childhoods, and futures.
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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 | 0.023 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.066 | 0.049 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.009 | 0.018 |
| Insufficient payload (model declined to judge) | 0.009 | 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".