Banished: The New Social Control in Urban America By Katherine Beckett and Steve Herbert Oxford University Press. 2010. 216 pages. $74 cloth, $19.95 paper
Bibliographic record
Abstract
Officials have classified approximately half of Seattle, including the entire downtown, as an illegal drug area. How could drug dealers have spread so widely in this progressive, postindustrial city? The answer is paradoxical, in that it is somewhat reassuring about the apparent annexation of Seattle by the drug trade, but unsettling about broader trends in the dynamics of social control in urban America. The expansive scope of Seattle's official “high drug” areas is not an indication of the extent of drug use or sales in that city. Instead, this high drug designation is one component in a larger regulatory structure designed to empower the authorities to exclude individuals who have received Stay Out of Drug Area (SODA) orders. These orders are imposed by judges or corrections officers on individuals on probation or parole who have been convicted of drug offences, mandating that they cannot enter designated areas. Such orders are just one of several creative developments in social control designed to regulate the configuration of human populations in urban spaces and which are the focus of this important book. Other initiatives include Stay Out of Areas of Prostitution (SOAP) orders, which are given to those charged with prostitution-related offences (both clients and sex-trade workers), again mandating that such individuals do not enter such officially designated areas. Likewise, parks exclusion orders allow police and park officials to immediately remove people from parks for crimes and minor infractions of park rules, and to ban them from some of or all the public parks for up to 1 year. Finally, and perhaps most legally innovative, are trespass exclusion provisions, which allow property owners (such as mall owners) to authorize the police to exercise trespass powers on their behalf. This permits the police to remove and ban from such property individuals that officers deem to be undesirable.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.053 | 0.012 |
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".