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Lifelong Learning

2009· article· en· W4249445762 on OpenAlexaff
Jo‐anne E Brien

Bibliographic record

VenueJournal of Pharmacy Practice and Research · 2009
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsDoug Bragg Enterprises (Canada)
Fundersnot available
KeywordsMedicinePharmacyLibrary scienceLifelong learningMedical educationFamily medicineLawPolitical science

Abstract

fetched live from OpenAlex

There is much focus, appropriately, on the development and delivery of university curricula, so we can 'guarantee' the future of the profession. Reading the academic literature on educational theory and practice, across the health disciplines, reveals active, critical, and robust processes searching for improved educational and professional outcomes. There is development of an evidence base for best-practice teaching and learning. There are excellent resources in Australia, for example, the National Patient Safety Framework, to facilitate integrating basic knowledge of facts into clinical and professional skills development. ewer technological support can contribute to the array and the multiple modes of delivery of education, and may be exciting and more accessible for students. The National Prescribing Curriculum materials, which are online modules provided by the National Prescribing Service for pharmacy, medical and nursing students are excellent examples. n the recent Journal of Clinical Pharmacology and Therapeutics, there is a commentary on teaching therapeutics in US medical schools. In the current US accreditation guidelines for the Association of American Medical Colleges, six core competencies are cited as required for safe and effective prescribing: medical knowledge; patient care; interpersonal skills and communication skills; professionalism; practice-based learning environment; and systems-based practice

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.350
GPT teacher head0.597
Teacher spread0.247 · 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 teacher head, not a consensus.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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