Bibliographic record
Abstract
C J H P – Vol. 56, No. 4 – September 2003 J C P H – Vol. 56, n 4 – septembre 2003 Although it has been suggested that these changes merely reflect a profession that is trying to redefine itself, I see them more as components in a process of continuous improvement: such efforts are required to meet both the changing needs of our patients and the demands of society at large. In particular, the demands of society are increasing exponentially. Over the past year, the Romanow report, the Kirby report, common drug review, and many regional initiatives have highlighted the potential needs and demands of society with regard to health care. The increased provision of home-based care, concerns about patient safety, and primary health care reform are only some of the challenges that hospital pharmacists continue to address day-to-day. Others include pharmacy specialization, pharmacist prescribing, implementation of new technology, and staff shortages. As a result of these influences, many institutions and provincial health ministries are reviewing their regulations to optimize use of pharmacist skills. Given the changes now taking place in society and more specifically in health care, I feel that my professional experiences will help me to draw attention to pharmacists’ potential impact. I have witnessed pharmacists in various practice sites proposing, implementing, and refining programs and policies that aim to increase the effectiveness and value of pharmacist interventions. In the position of President Elect, I can help to identify further changes that are INTRODUCING CSHP’S PRESIDENT ELECT
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 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.060 | 0.020 |
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".