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Record W2046946129 · doi:10.1080/13561820802028337

Developing leadership in rural interprofessional palliative care teams

2008· article· en· W2046946129 on OpenAlexaffabout
Pippa Hall, Lynda Weaver, Richard Handfield-Jones, Maryse Bouvette

Bibliographic record

VenueJournal of Interprofessional Care · 2008
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychological interventionNursingMedical educationWork (physics)Health careNeeds assessmentService (business)PsychologyMedicinePublic relationsSociologyPolitical scienceBusiness

Abstract

fetched live from OpenAlex

This project brought together community-based practitioners and academics to develop and deliver interventions designed to enhance the leadership abilities of the designated leaders of seven rural/small town-based palliative care teams. Members of these community-based teams have already gained recognition for their teams' leadership and service delivery in their communities. All of the teams had worked closely with most members of the academic team prior to this project. The team members participated in a needs assessment exercise developed by the Sisters of Charity of Ottawa Health Service and University of Ottawa academic team. Results of the needs assessment identified leadership qualities that had contributed to their success, as well as their needs to further enhance their individual leadership qualities. The team effort, however, was the most important factor contributing to the success of their work. The interventions developed to address the identified needs had to be adapted creatively through the collaborative efforts of both the community and academic teams. The educational interventions facilitated the integration of learning at the individual and community level into the busy work schedules of primary health care providers.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.003
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 head0.133
GPT teacher head0.458
Teacher spread0.326 · 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 designObservational
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

Citations12
Published2008
Admission routes2
Has abstractyes

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