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Record W7133086875

What form of collaboration is best for nursing?: qualitative case studies comparing college-university partnerships

2007· dissertation· W7133086875 on OpenAlexaboutno aff
Cassandra Mary Thompson

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipGovernment (linguistics)Qualitative researchInterpretation (philosophy)Conceptual frameworkQualitative propertyBest practice
DOInot available

Abstract

fetched live from OpenAlex

Collaboration among colleges and universities has been a topic of discussion for decades, with government, consumers and employers voicing support for seamless education, while maintaining the binary system enjoyed in Ontario. Although the literature review provides types of collaborations and elements of successful relationships, there is little published research on the lived experiences of senior faculty and administrators in any Ontario college-university partnerships, specifically, Collaborative Nursing. The purpose of this study is to explore the lived experiences of senior faculty and administrators, the challenges, barriers, and successes, and to establish whether one form of partnership is best for Collaborative Nursing Programs in Ontario. The goal is to elucidate fundamental components of successful relationships; thereby, providing a framework for developing and maintaining future partnerships, regardless of program. Key components of this study include a review of college-university cooperations, types of partnerships agreements, and theoretical concepts explaining successful relationships and predictive problems. The background chapter discusses Ontario's binary system, the evolution of nursing education, and the role of the provincial government in these initiatives. Incorporating a mixed methodology, quantitative data was collected from 17 colleges and 7 universities responding to the survey. Utilizing a naturalistic qualitative approach of inquiry and criteria-based sampling, 30 individuals participated in the four case studies. From the analysis and interpretation of the findings, it was learned that, although college and university professors and administrators were committed to the joint-program and the entry-to-practice requirements, relationship development was neither smooth nor easy. In comparing the four cases to the conceptual framework, it was found that most partnerships did incorporate some success elements, and many struggled with predictive problems in institutional differences, inflexibility, and conflicting external directives. In spite of their difficulties, differences in opinions and approaches, participants supported the concept of partnerships and joint-program delivery. It was discovered that partners who incorporated many of the conceptual elements, had open and honest communication, and diligently worked through differences, reaped successful relationships. Recommendations promote the use of the conceptual framework in developing and sustaining successful partnerships; several support cooperation between colleges and universities in overcoming barriers. Collaboration is a brilliant concept! (PsycInfo Database Record (c) 2020 APA, all rights reserved)

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)0.041
metaresearch head score (Gemma)0.056
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 score0.041
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0230.016
Scholarly communication0.0100.009
Open science0.0040.014
Research integrity0.0040.004
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 head0.279
GPT teacher head0.614
Teacher spread0.336 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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