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Record W2313431081 · doi:10.1177/1043659611423832

Putting the World as Classroom

2012· article· en· W2313431081 on OpenAlexaffabout
Louise Racine, Peggy Proctor, Lisa M. Jewell

Bibliographic record

VenueJournal of Transcultural Nursing · 2012
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicinePsychologyMedical education

Abstract

fetched live from OpenAlex

This article focuses on the description of an educational initiative, the Interdisciplinary Population Health Project (IPHP) conducted in the academic year of 2006-2007 with a group of nursing and health care students. Inspired by population health, community development, critical pedagogy, and the inequalities imagination model, students participated in diverse educational activities to become immersed in the everyday life of an underserved urban neighborhood. A sample of convenience composed of 158 students was recruited from 4 health disciplines in a Western Canadian university. Data were collected using a modified version of the Parsell and Bligh's Readiness of Health Care Students for Interprofessional Learning Scale. A one group pretest-posttest design was used to assess the outcomes of the IPHP. Paired t tests and one-way analyses of variance were used to compare the responses of students from different academic programs to determine if there were differences across disciplines. Findings suggest that students' readiness to work in interprofessional teams did not significantly change over the course of their participation in the IPHP. However, the inequalities imagination model may be useful to enhance the quality and the effectiveness of fieldwork learning activities as a means of educating culturally and socially conscious nurses and other health care professionals of the future.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.474
Teacher spread0.431 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2012
Admission routes2
Has abstractyes

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