Bibliographic record
Abstract
There is an absence of systematic evidence internationally on the extent of police violence, including lethal violence, against people with disabilities and mental ill-health. However, we know from individual cases and research data that the problem is extensive. Some of the most well-known police killings in the US which spurred the BLM movement involved Black Americans with disabilities, as has also been the case with deaths of Indigenous, Black, and people of colour in Canada and Australia. There is extensive police intervention into the lives of people with mental ill-health and cognitive impairments, and policing is a key part of the disablist processes of state control. The policing of disability is not a new phenomenon, but it has intensified with the neoliberal contraction of social support and the growth of the carceral state. Further, police decisions affecting people with disabilities compound through the carceral system, often justifying more extreme legal measures. As will be evident in this chapter, it is impossible to conceptualise policing without understanding its dis/abling effects. Centring disability is fundamental to the Defund the Police project and abolitionism more generally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".