Urban elderly women and fear of crime, a sociological analysis
Bibliographic record
Abstract
As Canadians are exposed to more frightening images of crime, violence and victimization, it is not surprising that fear of crime is believed to be increasing. Stereotypical images of "vulnerable" elderly women who are "paralyzed" with fear and have become "prisoners in their own homes" have contributed to the assumption that this segment of our population is the most fearful. The purpose of this study was to explore the experiences of fear of crime among a group of elderly women, aged 65 and older, living alone in an urban environment. Using qualitative methodology, this research relied on in-depth, semi-structured interviews with 20 women from Manitoba, Canada. Thematically, safety awareness emerged as a more appropriate conceptualization of the concern, worry and fear associated with personal safety and the safety of others. While these levels of safety awareness were not found to be salient problems for the participants, accommodations to safety were extensive. An exploration of the shape of fear revealed the characteristics of fear and identified the signs of alarm frequently associated with fear. Theoretically, the concept of safety awareness was situated within the social disorder perspective and Goffman's (1971) conceptual framework of normal appearances. The limitations associated with traditional fear of crime measures are discussed and recommendations made regarding future research and the need for more appropriate measurement. The implications of this research address the environmental and social factors associated with fear. Practical suggestions are made concerning the way in which elderly women respond to fearful situations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".