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Recruitment and retention of Canadian undergraduate psychiatric nursing faculty: challenges and recommendations

2011· article· en· W1930603547 on OpenAlexaffabout
Patrick J. Morrissette

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2011
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsBrandon University
Fundersnot available
KeywordsNursingMEDLINEMedicinePsychologyPsychiatryMedical educationPolitical science

Abstract

fetched live from OpenAlex

Accessible summary • Adverse public attitudes and stigma associated with the psychiatric population and their professional mental health providers can directly impact career choices among prospective nurse educators. • Geographical restrictions and the limited development and recognition of psychiatric nursing may hinder the recruitment of prospective nurse educators. • A coalition between the Canadian Nurses Association and the Registered Psychiatric Nurses of Canada may assist recruitment efforts. • The tenure and promotion process becomes particularly important for junior faculty within psychiatric nursing programmes. The education of psychiatric nurses in Canada has gradually evolved since its inception early in the 20th century. The most obvious advancement has been a move away from institutionally based training to undergraduate university preparation. Associated with this advancement is the ongoing challenge of recruiting and retaining qualified nurse educators. This essay addresses external factors (e.g. title disparity, association affiliation, societal perception of psychiatric nursing and professional identity) and internal factors (e.g. career transition and tenure and promotion) that influence faculty recruitment and retention. Existing challenges and recommendations designed to enhance recruitment and retention efforts are outlined.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.877
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.203
GPT teacher head0.459
Teacher spread0.256 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations6
Published2011
Admission routes2
Has abstractyes

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