Bibliographic record
Abstract
Hepatitis C (HCV) prevalence rates in prisons are even higher than HIV prevalence rates. Studies undertaken in the early and mid 1990s in Canadian prisons revealed rates of between 28 and 40 percent, and rates continue to rise. In one federal prison, 33 percent of study participants tested positive in 1998, compared to 27.9 percent in 1995; and at the Burnaby Correctional Centre for Women in British Columbia, over 78 percent of 69 inmates tested for HCV between 1 January 1996 and 8 August 1996 were seropositive. Similar figures are reported from other countries, including Australia. This raises many challenges for prison systems: how best to provide care and treatment to HCV-positive inmates; and how to prevent the further spread of HCV. Most HCV-positive inmates come to prison already infected, but the potential for further spread is high: HCV is much more easily transmitted than HIV, and transmission has been documented in prisons in several countries, including Canada. In Australia, an action plan for the surveillance and prevention of HCV in prisons has been developed as a result of meetings held in 1998 and 1999. We reproduce here the executive summary of the plan.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".