MétaCan
Menu
Back to cohort
Record W4361272836 · doi:10.1177/08943184221150265

A Conceptual Model for Professional Identity in Nursing: An Interdependent Perspective

2023· article· en· W4361272836 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

VenueNursing Science Quarterly · 2023
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsRegistered Nurses' Association of Ontario
Fundersnot available
KeywordsInterdependenceConceptual modelAccountabilityIdentity (music)Content analysisAction (physics)SociologyPerspective (graphical)Process (computing)PsychologyEpistemologyPolitical scienceComputer scienceSocial scienceLawPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

The purpose of this initiative was to define the development, verification, and evolution of the conceptual model for Professional Identity in Nursing. This action research design occurred over two phases, utilizing observations, a modified Norris process for model development, and focus groups. Analysis consisted of conventional content analysis and the Fawcett method for conceptual model analysis and evaluation. The model was modified, and results are presented based on the model's philosophical underpinnings, content, socialness, and evolution. The model resonates with nurses both in the United States and internationally. The interdependency shown in the model encourages collaboration, accountability, and sustainability within the profession and society.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.004
Open science0.0010.000
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 head0.061
GPT teacher head0.441
Teacher spread0.381 · 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