Questions of governance and accountability
Bibliographic record
Abstract
The contemporary mixed economy of visible patrols and the pluralisation of policing demand robust forms of governance, regulation and accountability that are fit for the tasks required of them. In the conclusion to its Discussion Paper, the Law Commission of Canada posed the following crucial question: What are the best governance mechanisms to ensure that policing is delivered in accordance with the democratic values of justice, equality, accountability and efficiency? (Law Commission of Canada, 2002, p 56) Demands for security, given their subjective nature and future orientation, are not always in keeping with concerns for justice. Private security strategies and social justice are not necessarily congruent, though neither are they mutually exclusive. Moreover, the growing market for additional security and policing has produced an unequal distribution. While some areas have a surfeit of policing and security, others experience a policing deficit. Access to enhanced security (often through the market) is primarily determined by wealth as well as the financial and organisational capacity of groups and businesses to club together to purchase additional security. This raises concerns that policing may become greater in affluent areas, where people have the loudest voices, the largest political influence and the deepest pockets. One of the central paradoxes of crime prevention and security is found in the often inverse relationship between activity and need (Crawford, 1998), and hence, security tends not to be concentrated where most needed. The inequitable distribution of policing in favour of affluent areas challenges (both central and local) governments to think creatively about how to respond to the security deficit experienced in some of the poorer parts of the country.
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 | 0.018 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.058 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".