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Record W4404296506 · doi:10.29173/cjen271

To be an employer of choice

2001· article· en· W4404296506 on OpenAlexaffvenue
Janet B. MacDonald

Bibliographic record

VenueCanadian Journal of Emergency Nursing · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsMontreal General Hospital
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Powell said:"Organizations don't really accomplish anything.Plans don't accomplish anything either.Theories of management don't much matter.Endeavours succeed or fail because of the people involved.Only by attracting the best people will you accomplish great deeds" (1996).How to be an employer of choice for the brightest graduates and the best, expert, specialty nurses is the challenge for nurse leaders of the new millennium.The nursing shortage has arrived.With it comes a multitude of factors that have stretched the health care system and challenged all health care employees.It may read as hopeless, but do not despair!The environment for nursing staff has become competitive.This is not a bad thing.It simply requires that leaders of organizations, divisions and services ensure that their environment is a great place to work.This article may help you to rethink your strategies in order to become an employer of choice.The nursing shortage is real.We face the 'retirement wave' as the percentage of RNs under 30 years of age shrinks at a constant rate from 25% of the nursing population in 1980 to 9% in 1996, and the average age of RNs increases from 40.3 in 1980 to 44.3 in 1996.Concurrently, there is declining enrollment in nursing schools as more people choose professions with increased wages and better working conditions.Specialty nurses are becoming an elusive breed where it can take as long as 90 days to fill vacancies in areas such as emergency, oncology, intensive care and

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.062
GPT teacher head0.292
Teacher spread0.231 · 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.

Study designNot applicable
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
Published2001
Admission routes2
Has abstractyes

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