Bibliographic record
Abstract
This study explores the creation and proliferation of urban entertainment destinations i n two Vancouver neighbourhoods - Gastown and Granville Mall - and the effect that these spaces are having on the delivery of urban policing services. This analysis provides a basis for a critique of both the 'broken windows' thesis and consumer culture. Urban entertainment destinations (UEDS) are sites that utilize forms of entertainment as a means of retailing goods and services. Unlike traditional notions of the city, site operators, and increasingly consumers, view these areas solely as spaces of consumption linked to pleasure. However, the marketing of many of these sites as pleasure spots is problematic for site operators because of the pre-existence of various forms of 'urban blight' that are commonly associated with the inner city. In order to reduce, or eliminate, a number of 'quality of life' issues that plague retailers and consumers, such as panhandling, graffiti, squeegees, street youth, and so on, business improvement associations (BIAs), which function roughly as site operators, demand an increased police presence. To augment existing public policing programs in their areas, many BIAs are also contracting private security services to engage in 'broken windows'-style policing in public spaces. Many of these services work cooperatively with public programs. The thesis advances three propositions. First, urban entertainment destinations generate demands for both increased and diversified forms of policing. Second, these demands for policing can be traced to modern consumption patterns and the mass media. Third, these demands can translate into 'policing' practices that are not centered around crime prevention or other strategies commonly associated with policing per se, but rather have more to do with creating and maintaining images of safety and 'risklessness' in sites frequented by consumers.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".