Observing the Observers: Researching Surveillance and Counter-Surveillance on 'Skid Row'
Bibliographic record
Abstract
Using empirical research drawn from field studies on the policing of 'skid row' communities, this paper illustrates some of the theoretical, methodological and ethical problems that confront the researcher who studies surveillance and counter-surveillance within these contested settings. We begin by noting how, with the increasing use of the 'broken windows' policing model to regulate deviant individuals and to secure derelict urban spaces, researchers may be implicated in the use of surveillance and counter-surveillance by community stakeholders. Drawing examples from direct and covert field observations, field notes, and photographs, we demonstrate that there is a significant potential for the researcher to become identified as an agent of surveillance, and as a potential target of counter-surveillance, within such settings. We conclude by considering some of the theoretical, methodological and ethical implications of the researcher's complicity in these dynamics for both the conduct of surveillance studies in general, and for urban fieldwork in particular.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".