Setting Aside Criminal Convictions in Canada
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
Expunging a criminal conviction in the United States is a rare event and often limited to persons who committed offenses as juveniles or adult misdemeanants. Criminal convictions in Canada, however, are routinely set aside through pardons after offenders have demonstrated a period of crime-free behavior. Sealing an offender’s criminal record, the practice in Canada, is a significant step in his or her reentry into society and official acknowledgment of society’s forgiveness. This exploratory study of pardons in Canada has two clear findings: First, despite the relatively easy process, few individuals with criminal records make application for pardons. Second, of those who do apply, few applications are ever denied, and a very small percentage of successful applicants reoffend. Although setting aside criminal convictions seems inconsistent with the increasing use of collateral consequences for U.S. offenders, taking this approach might contribute to increased public safety in the long term by easing offender reintegration.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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