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Record W4241084602 · doi:10.3821/145.2.cpj51

Missed Opportunity

2012· article· en· W4241084602 on OpenAlexvenueaboutno aff
Thuan Nguyen

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Missed opportunityThe analysis by Rosenthal et al. of the profession's response to Bill 16 in Ontario should be required reading in pharmacy curricula across the country.After all, students should know something about the culture of their chosen profession.For all the talk of moving forward, of expanded services and a new model of practice, it is all just that: talk.The majority of pharmacists do not have the confi dence or the commitment to embrace the role of "carers of patients."When faced with a crisis that threatens the bottom line, but with an opportunity to reshape the raison d'être of the profession, many pharmacists instead clung helplessly to the past, to that safety blanket we call dispensing.Perhaps it is fear of the unknown that pushes pharmacists and pharmacy organizations to so steadfastly embrace the status quo.Perhaps it is a misplaced sense of security.Many in the profession love to point to the fact that year after year, pharmacists rank near or at the top of the Ipsos Reid poll of most trusted profession (see page 55).Would we stand so tall in the public's eyes, I wonder, if they ever realized that the most trusted profession is more concerned with "pharmacist," "pharmacy" and "professional allowances" than it is with "patient care"?Public perception can change quickly; our profession apparently cannot.

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)0.005
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.429
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0080.007
Open science0.0030.011
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.4290.186

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 head0.146
GPT teacher head0.413
Teacher spread0.267 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2012
Admission routes2
Has abstractyes

Explore more

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