Full-time work for nurses: employers’ perspectives
Bibliographic record
Abstract
AIM: To examine an employer response to a government employment policy, the Nursing Graduate Guarantee (NGG), over a 2-year period (2008-2009 and 2009-2010). BACKGROUND: Healthcare organizations rely on a stable supply of nurses to meet their staffing needs. However, employment trends have indicated a propensity for part-time employment. The NGG was created to stimulate full-time employment of new graduate nurses in Ontario, Canada. METHODS: A mixed methods design was used, which included online surveys and focus groups. All healthcare providers (n = 1198) were surveyed in 2008-2009 and 2009-2010. Each year, a sample of NGG employers participated in sector-specific focus groups. RESULTS: Approximately 20% of potential healthcare employers participated in the NGG. Reasons for non-participation included lack of awareness of the initiative and lack of full-time jobs. Barriers to offering full-time employment to new graduates included lack of full-time vacancies and budget constraints. CONCLUSIONS: Employers perceive flexible staffing practices as a way to contain personnel costs but often at the expense of a stable full-time nursing workforce. IMPLICATIONS FOR NURSING MANAGEMENT: This research contributes to an understanding of employers' perspectives on full-time hiring and participation in a government employment policy.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".