Bibliographic record
Abstract
Discussions about harm reduction have been in the news on and off for the past few years — largely because of Insite, North America's first safe injection site located in Vancouver, BC, and the legal cases surrounding it.1 When the Supreme Court of Canada ruled last September in favour of the continued operation of Insite (and against the federal Conservative government ministers who wanted to halt its operation as part of their removal of harm reduction elements from their anti-drug strategies), many of those cheering were health professionals who support the harm reduction model as an important component of public health.2 For those unsure of what harm reduction is (and isn't), it is a public health concept with the primary goal of decreasing the negative consequences, i.e., harms, from the use of drugs (or alcohol, tobacco and even high-risk sexual practices) to both the individual involved and society at large.3 Harm reduction is not the promotion or encouragement of illicit drug use or other addictive behaviours. It is usually accomplished using a step-wise approach, aiming to implement the easiest, most realistic goals first.4 Advocates of the method realize that abstinence may not be a realistic or even desirable goal for some users, particularly in the short term, although many clients of harm reduction programs ultimately do enter abstinence or detoxification programs. The benefits of such programs have been well documented in published research and include improvements to the health of individuals and their communities, as well as savings to the health care system.5,6 In this issue of CPJ, you will find 2 interesting articles addressing the role of pharmacists in harm reduction programs (see pages 123 and 124). In many instances, pharmacists are already participants in harm reduction efforts such as needle exchange programs and opioid substitution therapy without fully recognizing the public health benefits of their work. As pharmacist Andrea Fernandes found, it is possible to overcome any initial concerns to find practice in an addiction clinic fulfilling and rewarding.7 With a recent report recommending the implementation of supervised injection facilities in Toronto and Ottawa8 and demands for similar services in other parts of the country, it's a great time for pharmacists to become more familiar with the opportunities in this expanding practice area. As our authors conclude, future research efforts should be directed at evaluating the effectiveness of pharmacists and pharmacies in delivering harm reduction interventions.9 Let us know what you think of this or any issue — your feedback is always welcome! Contact ac.stsicamrahp@neellikr.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.355 | 0.118 |
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".