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Record W7096559273

Canadian Nurses by the Year 2000

2016· article· en· W7096559273 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsNurse educationVariety (cybernetics)Health careOccupational health nursingTask (project management)Promotion (chess)Community healthHealth promotionTeam nursing
DOInot available

Abstract

fetched live from OpenAlex

The directors of the Canadian Nurses' Association (CNA) have unanimously endorsed the concept of university preparation as the minimum requirement for nurses entering the profession by the year 2000. A task force has been set up by CNA to develop strategies so that the goal for the year 2000 can be reached. At the provincial level, seven provinces to date have voted to support the national association's position and the remaining three provinces are currently studying the feasibility of such a change. The expanding role of the nurse in the health care delivery system has created the need to prepare a liberally educated person to function as a professional nurse in a variety of nursing roles and health care settings. University nursing education is designed to prepare graduates for: caregiving which is the major task of nursing both in the hospital and in community health agencies; for management and leadership in head nurse and supervisory positions; for health promotion as practiced in schools, homes and in clinics; for teaching and counselling which is inherent in almost every patient care situation; and in health and illness screening, a recently acquired and complex nursing responsibility (Kramer,

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)0.005
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: none
Teacher disagreement score0.916
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0080.001
Scholarly communication0.0060.001
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0490.013

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 head0.009
GPT teacher head0.263
Teacher spread0.254 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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