Bibliographic record
Abstract
This article reflects on the confession as a traditional focal point of criminal law and penal theories. Specifically, it questions the privileged status traditionally conferred to the confession within the hierarchy of legal proof and punishment as a remnant of Christian influence which should be made visible. This reflection draws on the case of Robert Latimer, one of the few judicial cases historically to have polarized Canadian public opinion. After serving seven years in a federal penitentiary for the ‘mercy killing’ of his 12-year-old severally handicapped daughter, Saskatchewan farmer, Robert Latimer, was denied day parole by the National Parole Board of Canada on 5 December 2007. Despite in-prison psychological and parole reports confirming Latimer’s low risk to reoffend, parole board members denied his request on the apparent sole basis that he had not developed sufficient remorse. This case highlights how remorse, as a particular discursive transaction, is an obligatory passage point or an oral corroboration indispensable to complete the written demonstration (i.e. psychological and parole reports) of an offender’s successful integration of the ‘truth’ about her and her crime. Hence, remorse may constitute the only valuable way for offenders to re-take their place within the ritual of ‘Truth’ production.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".