Back to ‘things themselves’: breaking the cycle of misrepresentation when serving African Canadian youth
Bibliographic record
Abstract
Bureaucratic discourses informed by legacies of slavery and colonisation create traumatising experiences among African Canadian youth in social, educational and law-enforcement institutions in Canada. These discourses create the already-known-people paradigm and are then exacerbated by the effects of neoliberal policies and managerialist administrations to produce an unfortunate social condition in which system professionals discount what these youth say about experiential marginality and social injustice. This means that African Canadian youth end up being understood by system professionals from administrative discourses or from historical assumptions. Using phenomenology, I argue in this article that focusing on the experiences of these youth in time when assessing or making decisions about them may help to reduce stereotyping and stigmatisation, and to highlight normalised social injustices. Consequently, focusing on behaviour-in-time as opposed to behaviour-in-discourse may allow system professionals to operationalise administrative discourses without downplaying behaviour-in-time, which is important in service provision.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.062 | 0.029 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| 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".