Bibliographic record
Abstract
Vancouver's much-anticipated safe injection site (SIS), the first in North America, was nearly at full capacity less than 3 months after opening Sept. 15. Site staff are supervising an average of 450 injections daily; full capacity is 600 visits (see CMAJ 2003; 169 [8}: 759-63). There are an estimated 4000 injection drug users in the city's Downtown Eastside. Mark Townsend of the Portland Hotel Society, which runs the SIS with the Vancouver Coastal Health Authority, says initial fears that patrolling police officers and security cameras would deter drug users have proved unfounded. He also attributes the high usage to the experienced staff, extensive street-level and word-of-mouth publicity prior to the opening. So far, 25 users have experienced adverse reactions on site and required assistance. At least 33 users have been referred to detoxification services. Nurses are also carrying out a lot of wound and other basic medical care. Townsend says he hopes that the SIS's 3-year research project will answer questions about the site's early success. Meanwhile, in the short term, he would like to see extended hours, a second location and more detoxification facilities.— Heather Kent, Vancouver Figure. About 90% of injection drug users are still on the streets. Photo by: Canpress
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.305 | 0.086 |
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".