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Record W2762598403 · doi:10.1111/ijn.12607

Conducting research through cross national collaboration

2017· article· en· W2762598403 on OpenAlex
Mary K. Steinke, Melanie Rogers, Daniela Lehwaldt, Kimberley Lamarche

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Nursing Practice · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsAthabasca University
Fundersnot available
KeywordsProcess (computing)Nursing researchNursing practiceHealth careNursingPublic relationsMedical educationKnowledge managementPsychologyEngineering ethicsMedicinePolitical scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

AIM: To explore the collaborative nature of an international research project with other advanced practice nurse researchers and critically analyse the process. BACKGROUND: Research within the nursing community is recognized internationally as important to ensure that nurses participate in cutting-edge health care and promote evidence-based practices, yet there is little detail found in literature on how a successful collaborative relationship is initiated and conducted in advanced practice research. DESIGN: Discussion paper: The purpose of this paper is to discuss the process of collaboration on a research study among advanced practice nurses from four countries who are members of an international organization. IMPLICATIONS FOR NURSING: The collaborative process in international nursing research can be challenging and rewarding. It is important to remember that there is a relationship between the complexity of the study and the time required to complete it. Keys to success include following established guidelines. CONCLUSION: This project was a valuable experience in developing collaborative relationships as well as creating partnerships for future research to build on the knowledge gained. The authors' linkages to universities facilitated their participation in the research and completion of the ethical review processes. The use of social media and university resources was indispensable.

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.

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)0.015
metaresearch head score (Gemma)0.074
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.700
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.074
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.006
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.792
GPT teacher head0.767
Teacher spread0.025 · 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