Dangerous disciplines: Understanding pedagogies of punishment in the neoliberal states of America
Bibliographic record
Abstract
Abstract Public schools deploy a range of processes and practices that help constitute the formation and legitimation of certain knowledges, relationships, skills, values and, ultimately, subjectivities. School discipline regimes are one of these practices. Exercising their power through pedagogical modes of address, these regimes are currently organizing relationships throughout school cultures that reflect the values and encourage role performances associated with neoliberal capitalism. This research paper describes and analyzes two widely used discipline regimes-zero tolerance/hyper-criminalization and positive behavior interventions and support (PBIS) -through Foucault’s theories of governmentality and biopolitics. These two regimes provide mirror images of the primary modes of punishing and disciplining under neoliberalism: criminalization and individualization. The paper will also explore how neoliberalism subjects schools to processes of enclosure, but also how schools themselves have become sites productive of neoliberal subjects through the content, values and interests embedded in the curricula of PBIS and criminalization which students must master.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| 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".