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Record W2323811119 · doi:10.1177/1715163513494592

Alberta College of Pharmacists confirms it will proceed with inducements ban but enabling mechanism still under review

2013· article· en· W2323811119 on OpenAlexvenueaboutno aff
Kathie Lynas

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2013
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacyTimelinePharmacistPharmacy practicePublic relationsStatement (logic)Conflict of interestMedical prescriptionMedicinePolitical scienceBusinessPsychologyFamily medicineLawNursing

Abstract

fetched live from OpenAlex

After a few months of delay to digest a flood of comments on the issue, the Alberta College of Pharmacists (ACP) has confirmed it will not abandon plans to prohibit consumer inducements for prescription drugs and professional pharmacy services. The ACP first proposed banning coupons and loyalty programs in the fall of 2012—a move that prompted criticism by some patient groups and retailers. In late December of last year, the College said it needed more time to assess the complex issue and the extensive feedback it had received. In a statement issued April 18, 2013, the regulatory body stated it would go ahead with the proposed ban, noting that 75% of pharmacists and pharmacy technicians it surveyed support such action by the College. “This isn’t about any one pharmacy or any one type of reward. The prohibition would apply to all pharmacists, pharmacy technicians and pharmacies,” said Greg Eberhart, ACP Registrar, in the statement. “Pharmacists are making decisions about drug therapy; it’s not the same environment that we had 5 or 10 years ago. Our interest is around the practices of pharmacists and the new expectations and responsibilities they have. We want to make sure they are free from conflict.” The College is still considering the best mechanism for putting the ban into effect. It could be a new regulation, standard of practice or amendment to the Code of Ethics. No timeline for the change has been announced; the College says that will depend in part on which mechanism is to be used.

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)0.023
metaresearch head score (Gemma)0.056
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.545

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0130.005
Scholarly communication0.0170.005
Open science0.0050.003
Research integrity0.0300.021
Insufficient payload (model declined to judge)0.0620.030

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 head0.259
GPT teacher head0.433
Teacher spread0.174 · 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
GenreOther

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

Citations0
Published2013
Admission routes2
Has abstractyes

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