MétaCan
Menu
Back to cohort

Maturing Professional Selfhood through Body Mapping

2021· article· en· W3195168725 on OpenAlexaff
Colleen Maykut

Bibliographic record

VenueJournal of Health and Caring Sciences · 2021
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsMacEwan University
Fundersnot available
KeywordsIdentity (music)NarrativeDisciplineTransition (genetics)PedagogyProfessional developmentPsychologyQuality (philosophy)Health professionalsExpression (computer science)Medical educationSociologyHealth careAestheticsMedicineEpistemologyPolitical scienceArtComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Nursing education's fundamental goal is to prepare students to effectively transition into practice. Success in this endeavor occurs when the student has a clear sense of themselves as a professional in relationship with their peers and grounded in disciplinary knowledge. Faculty must intentionally create opportunities for students to explore and mature their professional selfhood (PSH) to assist in a smooth transition from academia to practice. Educational strategies which enhance the awareness and continued development of PSH as a birthplace for professional identity may enable the graduate to navigate the healthcare system, mitigate ethical dilemmas, and enhance the quality of life for those they care for and themselves. Aesthetic narratives could be utilized to engage students in the analysis of their PSH as an alternative beyond the dominant text as an expression.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
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 head0.050
GPT teacher head0.388
Teacher spread0.337 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Health and Caring SciencesSame topicEmpathy and Medical EducationFrench-language works237,207