Bibliographic record
Abstract
Walter S. Dekeseredy, Shahid Alvi, Martin S. Schwartz and Andreas Tomaszewski. UNDER SIEGE: POVERTY AND CRIME IN A PUBLIC HOUSING COMMUNITY. Lexington Books, USA, 2003,182 pp. $24.95 Softcover.An underlying premise of Under Siege is that Canada has concentrations of poverty and crime greater than those of the United States, a disquieting thought for Canadians. Poverty is also becoming increasingly concentrated in Canada's major urban areas. That poverty and crime share a common North American economic and residential pattern should not be as surprising since the housing and social welfare policies of both countries are slowly converging. Since the administrations of Mulroney and Reagan there has been more emphasis on private sector involvement in social housing and devolution from government involvement in the operation, maintenance and creation of such housing stocks. In Canada these include, non-profit cooperatives, non-profit NGO (termed third sector) housing and government owned or financed housing.Women are among the most vulnerable residents of public housing. Under Siege addresses the widely neglected issue of how endemic poverty and crime eats away at the fabric of resident's individual and collective lives. Along with women, members of minority groups, especially immigrants, and gays and lesbians, are continually subject to crimes of various types. One of the important contributions of this study is that it goes beyond middle class definitions of crime, e.g. auto theft, robbery, drug trafficking, and assault. Crimes that diminish self-worth, increase fear, and impose social controls through intimidation, are also dealt with. The umbrella term harassment does not quite do justice to what residents of public housing endure. Whether this harassment is sexual, racially or ethnically inspired, or stems from observed difference, the effect is to limit freedom of movement, force residents to plan their movements, and at night to be prisoners within their own homes. At home they may be subject to violence from acquaintances, friends and significant others.This study is intended to lay a foundation for further research in this area. The authors use quantitative methods, surveys and interviews to investigate the relationship between poverty and crime in West Town, the pseudo name given to the Ontario public housing estate they studied. This study seeks to provide some facts and figures, compensating for the minimised reporting found in certain crime and poverty statistics, such as the Quality of Neighbourhood Life Survey (QNLS). …
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".