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Record W2094465928 · doi:10.5737/1181912x123146148

A model for successful research partnerships: A New Brunswick experience

2003· article· en· W2094465928 on OpenAlexaffvenueabout
Karen Tamlyn, Helen Creelman, Garfield Fisher

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2003
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsGeneral partnershipPublic relationsWork (physics)Order (exchange)Political sciencePublic administrationBusinessEngineering

Abstract

fetched live from OpenAlex

The purpose of this paper is to present an overview of a partnership model used to conduct a research study entitled "Needs of patients with cancer and their family members in New Brunswick Health Region 3 (NBHR3)" (Tamlyn-Leaman, Creelman, & Fisher, 1997). This partial replication study carried out by the three authors between 1995 and 1997 was a needs assessment, adapted with permission from previous work by Fitch, Vachon, Greenberg, Saltmarche, and Franssen (1993). In order to conduct a comprehensive needs assessment with limited resources, a partnership between academic, public, and private sectors was established. An illustration of this partnership is presented in the model entitled "A Client-Centred Partnership Model." The operations of this partnership, including the strengths, the perceived benefits, lessons learned by each partner, the barriers, and the process for conflict resolution, are described. A summary of the cancer care initiatives undertaken by NBHR3, which were influenced directly or indirectly by the recommendations from this study, is included.

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)0.030
metaresearch head score (Gemma)0.022
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 score0.915
Threshold uncertainty score0.704

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0320.016
Scholarly communication0.0160.010
Open science0.0040.022
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0080.001

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 head0.337
GPT teacher head0.576
Teacher spread0.238 · 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

Citations2
Published2003
Admission routes3
Has abstractyes

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