MétaCan
Menu
Back to cohort
Record W2563773275 · doi:10.5430/jnep.v7n5p94

Men in nursing: The early years

2017· article· en· W2563773275 on OpenAlexvenueno aff
Martin Christensen

Bibliographic record

VenueJournal of Nursing Education and Practice · 2017
Typearticle
Languageen
FieldPsychology
TopicFamilies in Therapy and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsDemiseNursingHistory of nursingDominance (genetics)Nursing carePerspective (graphical)MedicineNurse educationPolitical scienceLaw

Abstract

fetched live from OpenAlex

Objective: Nursing is as old as mankind and the nature of what it means to be a man in nursing has a wide and varied history. Men have been at the forefront of nursing practice from before the birth of Christ – the first record of male nursing originates from ancient India. Slowly over time the image of the male nurse has given way to the dominance of women largely thanks to Florence Nightingale. The aim of this paper is to discuss the contribution men have made to the profession of nursing through the early years of nursing’s history in particular from 250BC to the early 1900’s.Methods and result: Design: A historical review. Data Sources: The search strategy included research studies both qualitatively and quantitatively, as well as anecdotal and discursive evidence from 1900-2015. Implications for Nursing: The predominance of the history of has always had a focus on the female perspective. Men have had played a significant part in the development of that history. Acknowledging the role men have contributed in developing and promoting nursing practice is equally as valid and as such should be recognised accordingly.Conclusions: Male nursing has had a varied history from the first recoded nursing school in 256BC to its slow eventual slow demise from the 1840’s. Records reveal the work of the male nurse was seen predominately within secular institutions and personified aspects of care that focused totally on patient wellbeing both physically and spiritually.

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: none
Teacher disagreement score0.728
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.079
GPT teacher head0.484
Teacher spread0.405 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nursing Education and PracticeSame topicFamilies in Therapy and CultureFrench-language works237,207