The Nexus of Post-Racialism, White Supremacy, and Misogynoir in Education
Bibliographic record
Abstract
Education is the state apparatus of elimination that seeks to suppress non-white, cis-gendered, and wealthy (in all forms of capital) students from being “productive” members of society. To uphold whiteness, education continues to evolve to incorporate various technologies of elimination, including policing (Dumas, 2016; Maynard, 2017a; McPherson, 2020). Though there is significant scholarship on anti-Blackness in education, sexism, and misogyny in education, the nexus of Black and girlhood is often neglected (Macías, 2015; McPherson, 2020). This chapter gives critical, academic, and reflexive space to assess misogynoir in Canadian education. In this chapter, I argue that formal educational spaces are a primary force responsible for the social and physical policing and surveillance of Black girlhood (Maynard, 2017b; 2017c; McPherson, 2020). To further specify my argument, I situate my lived experiences to contend that post-racialism enables state-sanctioned educational institutions, policy, and its actors to engage in the policing and surveillance of Black girlhood in “invisible” yet pernicious ways (Collins, 1999; Goldberg, 2007; Maynard, 2017b; 2017c).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.030 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".