Principled Experiments in Just Being: From Police Oversight to Community Intersight
Bibliographic record
Abstract
ABSTRACT This article compares ideals and practices of police oversight in two very different contexts—settler colonial North America and “post” colonial South Asia—to interrogate fundamental principles underlying police oversight globally and to imagine new ways of working toward transformation. The analysis ultimately asks: how might we conceive new modes of engagement around community safety and governance in line with ideals of social justice as a global humanistic principle? Drawing inspiration from (1) a Gandhian ethics of “fidelity to being” and “unconditional equality” in Satyagraha praxis as a “religion of resistance” to sovereign command and (2) Haudenosaunee principles manifest in the Kayaneren'kó:wa (Great Law of Peace), I suggest we move away from demanding more or better police oversight bodies and turn instead toward creating institutions that foster “intersight” as spaces of exchange among community members, government officials, legal experts, and other stakeholders. Intersight may provide good‐faith forums for critical self‐introspection by all parties involved and, crucially, open‐minded and compassionate listening to others regarding what kinds of policing or other forms of collective action geared toward security, safety, and justice, may be needed in a particular community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.060 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.060 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".