Bibliographic record
Abstract
Purpose The purpose of this paper is twofold. First, it explains the current records management practices for Canadian criminal records. Second, it details the larger social and cultural implications of those practices, toward considering the role records management plays in long‐term sustainable offender rehabilitation outcomes. Design/methodology/approach This paper is based on a thorough literature review, which considered research on the history of Canadian criminal record management; current records management procedures for Canadian criminal records; and current Canadian social and cultural understandings of offenders, criminal records, and the relationship between criminal record management and public policy. Findings This paper finds that Canadian records management procedures for criminal records can have grave impacts on offenders' lives. Specifically, this paper explores how records management practices are shaped by the social norms and values embedded in public policy mandates, which ultimately appear to disrupt, rather than support, offenders' rehabilitation. Research limitations/implications This paper's research is limited by its current approach. Consequently, it encourages researchers to further develop its findings in the future, both domestic to Canada and internationally. Practical implications This paper includes implications that advocate for increased awareness about how public policy dictated records management procedures can limit offenders' ability to reintegrate into society. Social implications This paper addresses the grave social consequences and burdens offenders face when they are unable to seal their previous criminal record. Originality/value This paper addresses the need to study how offenders' rehabilitation is affected by the policy dictating the management of their criminal record.
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 | 0.013 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.023 | 0.030 |
| Science and technology studies | 0.026 | 0.007 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".