MétaCan
Menu
Back to cohort
Record W2318052747 · doi:10.3928/00220124-20151217-02

The Scholarship of Application: Recognizing and Promoting Nurses’ Contribution to Knowledge Development

2014· article· en· W2318052747 on OpenAlex

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

VenueThe Journal of Continuing Education in Nursing · 2014
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsUniversity of British ColumbiaGeorgian College
Fundersnot available
KeywordsScholarshipSituatedSociologyNursing researchEngineering ethicsMedical educationMedicinePolitical scienceNursingComputer scienceEngineering

Abstract

fetched live from OpenAlex

The generation of knowledge is fundamental to the practice of nursing and occurs through various forms of scholarship. Boyer recognized this and described knowledge production through research, integration, teaching, and application. The focus of this article is on the scholarship of application and its role in the development of nursing knowledge. Examples of achievement in the scholarship of application are provided with outcomes of work between community and education partners and innovative clinical practice changes. The scholarship of application is of particular importance to nursing as it bridges research, practice, and education, and documents and disseminates nursing knowledge to enable peer critique. Approaches for developing a climate of scholarship are discussed, including differentiating scholarly practice from clinical scholarship and how the scholarship of application is situated in practice arenas. The role of clinical scholars and clinical leaders and the continuing development of future scholars are proposed.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.337
Teacher spread0.330 · 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