Who Needs the Undercommons? Refuge and Resistance in Public High Schools
Bibliographic record
Abstract
This paper is a theoretical discussion of The Undercommons: Fugitive Planning and Black Study (Harney & Moten, 2013) as a contribution to critical education in public schools. The undercommons serves here as an epistemic device, or a way of seeing and knowing, in relation to public education. The function of this device is to establish an appreciative view of student survival and activist behaviours and to centre educational policy as a potential mechanism of student exclusion. I propose that the practice of inclusion in schools coexists with unacknowledged operations of exclusion. The undercommons is employed as a lens to make such mechanisms of disenfranchisement apparent. I advocate here for an extension of inclusive education which, in addition to targeted supports for particular demographic groups, must concern itself with more general practices of disenfranchisement.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.035 | 0.036 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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".