Constructing Identity and Drawing Lines: The Textual Work of Ontario’s Safe Streets Act
Bibliographic record
Abstract
Using the text of Ontario’s Safe Streets Act (legislation in effect since January 2000), the author examines the processes and techniques employed in social policy discourse to ascribe identity for purposes of organizing people and distributing power. The approach to social inquiry used in this analysis is Dorothy Smith’s formulation of institutional ethnography. The author begins by documenting her own reading, or text-reader conversation, of the press release heralding the advent of the bill, permitting exposure of the textual procedures used to interact with and draw in the discourses predominant in the ideological frame. Examination of the act itself reveals some of the identity ascriptions contained within. The author concludes with an analysis of the constitution and ascription of identity as a practice of power and social control. This study incorporates expansion on the discourses of moral regulation, social exclusion and moral panic as they are implemented to construct and organize certain socio-political identities, including the community member, the law-abiding citizen as a consumer and the offender.
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.
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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.043 | 0.060 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".