Media Frames of the Ontario Safe Streets Act: assessing the moral panic model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper assesses the “moral panic” framework of Stanley Cohen with reference to panhandling and squeegeeing in Ontario. There are four general tenets of the moral panic model, three of which can be said to have been documented in the case of panhandling in Ontario: a recognized threat (panhandling), a rise in public concern, and punitive control mechanisms established to eliminate the threat. This paper argues that the fourth tenet, a stereotypical presentation of the moral threat to the social order, has not been systematically analyzed, and therefore that is the task of this paper. Specifically, this paper examines the framing used by the mainstream print media in Ontario to construct the panhandling/squeegeeing problem. Articles and letters to the editor were sampled from two mainstream Ontario newspapers, the Toronto Star and the Ottawa Citizen, to examine the mainstream media’s framing of panhandling and squeegee cleaning.
 This sample was taken between 1995 and 2005, a timeframe which revolves around the implementation of the Ontario Safe Streets Act 2000, which is recognized as the punitive control mechanism designed to eliminate the threat of panhandling. The findings of this paper lead to the conclusion that panhandling in Ontario during the implementation of the Ontario Safe Streets Act does not constitute a classic moral panic by virtue of the role the media played. However, the evidence that punitive control mechanisms were established absent the support of the mainstream media suggests that a deeper understanding of the role of mainstream media as well as political interests is required with respect to framing moral panics.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it