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Record W1593368451 · doi:10.37333/001c.002001006

Experiences of Health System Preceptors and Faculty Advisors with Community Service-Learning Initiatives: Learning from the Dalhousie University Drug Use Management and Policy Residency Program

2014· article· en· W1593368451 on OpenAlexafffundabout
Sarah Bowen, Ingrid Sketris, Ethel Langille Ingram

Bibliographic record

VenueInternational Journal of Research on Service-Learning and Community Engagement · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsDalhousie UniversityUniversity of Alberta
FundersCanadian Institutes of Health ResearchDalhousie UniversityNova Scotia Health Research FoundationCanadian Health Services Research Foundation
KeywordsNova scotiaPharmacyMedical educationService (business)Service-learningMedicinePolitical scienceNursingPsychologyBusinessSociologyPedagogy

Abstract

fetched live from OpenAlex

From 2001 to 2011, an innovative approach to pharmaceutical policy and drug use management graduate education—the Drug Use Management and Policy Residency Program—was developed and implemented by the College of Pharmacy at Dalhousie University in Halifax, Nova Scotia, Canada. This in-depth qualitative assessment of the experience of faculty members and site preceptors who guided residents in their 17-week placements identifies components, characteristics, strategies, and principles associated with successful service-learning initiatives and provides guidance around the development of programs in other jurisdictions.

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)0.025
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.007
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 head0.134
GPT teacher head0.406
Teacher spread0.272 · 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 designQualitative
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
Published2014
Admission routes3
Has abstractyes

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