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Record W2201337277 · doi:10.1080/01621424.2015.1108892

“A More Rounded Full Care Model”: Interprofessional Team Members’ Perceptions of Home-Based Primary Care in Ontario, Canada

2015· article· en· W2201337277 on OpenAlexaffabout
Tracy Smith‐Carrier, Thuy-Nga Pham, Sabrina Akhtar, Mark Nowaczynski, Gayle Seddon, Samir K. Sinha

Bibliographic record

VenueHome Health Care Services Quarterly · 2015
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsMount Sinai HospitalKing's University CollegeHome and Community Care Support ServicesToronto Western HospitalUniversity Health NetworkUniversity of TorontoWestern University
Fundersnot available
KeywordsPrimary careNursingMedicineFamily medicinePsychologyGerontology

Abstract

fetched live from OpenAlex

This study explores interprofessional team members' perspectives and experiences providing home-based primary care (HBPC) in Ontario, Canada. Employing an inductive qualitative methodology using procedures informed by grounded theory, themes emerged in the data in relation to the benefits of the HBPC model, and the barriers associated with its provision, as well as the key components that enable or hinder interprofessional collaboration in the HBPC environment. This research deepens our understanding of the key features and processes of interprofessional teams providing high-quality care in the home.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.006
Scholarly communication0.0050.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.349
Teacher spread0.334 · 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.

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

Citations20
Published2015
Admission routes2
Has abstractyes

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