Bibliographic record
Abstract
BACKGROUND: More than 5 years ago, the Blueprint for Pharmacy developed a plan for transitioning pharmacy practice toward more patient-centred care. Much of the strategy for change involves communicating the new vision. OBJECTIVE: To evaluate the communication of the Vision for Pharmacy by the organizations and corporations that signed the Blueprint for Pharmacy's Commitment to Act. METHODS: The list of 88 signatories of the Commitment to Act was obtained from the Blueprint for Pharmacy document. The website of each of these signatories was searched for all references to the Blueprint for Pharmacy or Vision for Pharmacy. Each of the identified references was then analyzed using summative content analysis. RESULTS: A total of 934 references were identified from the webpages of the 88 signatories. Of these references, 549 were merely links to the Blueprint for Pharmacy's website, 350 of the references provided some detailed information about the Blueprint for Pharmacy and only 35 references provided any specific plans to transition pharmacy practice. CONCLUSION: Widespread proliferation of the Vision for Pharmacy has not been achieved. One possible explanation for this is that communication of the vision by the signatories has been incomplete. To ensure the success of future communications, change leaders must develop strategies that consider how individual pharmacists and pharmacies understand the message.
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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.243 | 0.072 |
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".