The Gendered, Misogynoiristic, and Colonial Genocidal Logics of Strip Searching
Bibliographic record
Abstract
Women with lived experience of strip searching have been calling for it to be banned as a practice for decades; however, it remains a routine practice in carceral settings such as prisons and jails. Given the mass incarceration of Indigenous women and disproportionate rate of Black women in federal prisons in Canada, an anti-racist and gendered anticolonial analysis of strip searching is warranted. Thus, this paper shares findings from conversations with 23 previously incarcerated women, the majority of whom are Black and Indigenous, about their experiences of being strip searched in prisons. The main theme throughout the conversations was that strip searching is sexual violence by the state. Furthermore, the harms of strip searching are gendered in that women are forced to remove their tampons and pads during menstruation to show guards. The paper also elucidates the ways in which strip searching enacts misogynoiristic and colonial genocidal logics historically rooted in projects such as Indian Residential Schools and the enslavement of Black women. It ends with a call for abolition feminist social work praxis by meeting the direct needs of women who are strip searched while also advocating for it to be banned as a practice.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.049 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".