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Record W1990499999 · doi:10.12927/cjnl.2012.22807

New Brunswick: Development of a Web-Based Orientation Program and Enhancing Senior Nurses' Mentoring Skills

2012· article· en· W1990499999 on OpenAlexaffvenueabout
Marise Auffrey, Monique Cormier-Daigle, Anne Gagnon-Ouellette

Bibliographic record

VenueNursing leadership · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsDr. Georges-L.-Dumont University Hospital Centre
Fundersnot available
KeywordsMentorshipUnit (ring theory)Medical educationNursingOrientation (vector space)PsychologyWeb applicationResource (disambiguation)MedicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This project to help new nurse recruits integrate into the hospital work environment had two components: the development of a new web-based orientation tool in French for new recruits and mentor training for more experienced nurses. The aim of the first component was to redesign delivery of the nursing orientation program by assessing individual needs of new recruits and developing "just in time" information sessions with online access and e-learning modules. The second component aimed to develop a voluntary mentorship training program for senior nurses that offered training on the role and responsibility of mentors. A total of 30 orientation modules were created as resources that could be adapted to the needs of each nursing unit and accessed online. Sixty nurse recruits used the programs. A mentor training program was developed, and 28 nurses were trained as mentors. The mentorship literature and guides, produced in French, will be a valuable resource for francophone nurses across Canada.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.122
GPT teacher head0.434
Teacher spread0.312 · 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 designObservational
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

Citations2
Published2012
Admission routes3
Has abstractyes

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