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Record W2325855859 · doi:10.1177/1715163515577693

Advocacy in pharmacy

2015· article· en· W2325855859 on OpenAlexafffundvenueabout
Luke Boechler, Robyn Despins, Jennifer Holmes, Jolene Northey, Cooper Sinclair, Matthew Walliser, Jason Perepelkin

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsGrassrootsPharmacistPharmacyHealth professionalsPublic relationsNursingProfessional servicesPharmacy practiceHealth careMedicineClinical pharmacyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Pharmacists are moving from traditional and technical dispensing roles to professional and clinical patient-centred services. They have shown that these new professional services have an essential and positive effect on patient outcomes. However, we must advocate for and promote these new services to 4 key groups—pharmacists, other health care professionals, patients and the community—or what is the point? This advocacy must begin at the grassroots, with the individual pharmacist, rather than relying solely on our professional organizations. It begins with the pharmacist eliminating the mystery of “behind the counter.” Both verbal patient interaction tips and nonverbal strategic communication tools can be developed and used to aid in this venture. We invite all pharmacists across Canada to take ownership of their evolving profession and to share ideas and collaborate with their colleagues. ■

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 imitation

Not 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.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.126
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.059
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0330.043
Scholarly communication0.0170.011
Open science0.0020.019
Research integrity0.0220.027
Insufficient payload (model declined to judge)0.0220.002

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.

Opus teacher head0.281
GPT teacher head0.474
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2015
Admission routes4
Has abstractyes

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