MétaCan
Menu
Back to cohort
Record W2275340788 · doi:10.1080/02701960.2016.1144599

Gerontology across the professions and the Atlantic: Development and evaluation of an interprofessional and international course on aging and health

2016· article· en· W2275340788 on OpenAlex
Phillip G. Clark, Lori E. Weeks, Graziella Van den Bergh, Shelley Doucet

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGerontology & Geriatrics Education · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of New BrunswickDalhousie University
FundersSenter for Internasjonalisering av Utdanning
KeywordsTeamworkMedical educationInterprofessional educationGeriatricsHealth carePresentation (obstetrics)MedicineNursingPsychologyGerontologyPolitical science

Abstract

fetched live from OpenAlex

The need for interprofessional teamwork and the global challenges for health care systems of dramatically increasing numbers of older adults have received increased recognition in gerontological and geriatrics education. The authors report on the pilot development of a hybrid course on aging and health for graduate-level health professions students from Norway, Canada, and the United States. International faculty from partnering universities developed, taught, and evaluated the course. Course assignments included online forum postings, reflections, and a problem-based learning group assignment and presentation. Directed readings and discussion included topics related to health care systems and services in the three participating countries, teamwork, and patient-centered care. To evaluate the course, quantitative and qualitative data were collected and analyzed. Results indicate a significant impact on student learning outcomes, including understanding of issues in international aging and health, attitudes and skills in teamwork, and application to clinical practice. This course clearly established the importance of developing innovative interprofessional educational experiences that respond to the increasingly universal impacts of aging populations on health and social care systems around the world.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.100
GPT teacher head0.516
Teacher spread0.417 · 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