Self-employed nurses as change agents in healthcare: strategies, consequences, and possibilities
Bibliographic record
Abstract
PURPOSE: The purpose of this paper is to report on ethnographic research that investigated how self-employed nurses perceive the contemporary healthcare field, what attributes they possess that facilitate their roles as change agents, what strategies they use to influence change, and what consequences they face for their actions, thus contributing to what is known about organizational change in institutionalized settings such as healthcare. DESIGN/METHODOLOGY/APPROACH: Focussed ethnography was used to explore self-employed nurses' work experiences and elucidate the cultural elements of their social contexts, including customs, ideologies, beliefs, and knowledge and the ways that these impact upon the possibilities for change in the system. FINDINGS: These self-employed nurses reflected on the shortcomings in the healthcare system and took entrepreneurial risks that would allow them to practice nursing according to their professional values. They used a number of strategies to influence change such as capitalizing on opportunities, preparing themselves for innovative work, managing and expanding the scope of nursing practice, and building new ideas on foundational nursing knowledge and experience. They had high job satisfaction and a strong sense of contribution but they faced significant resistance because of their non-traditional approach to nursing practice. ORIGINALITY/VALUE: Despite dramatic restructuring in the Canadian healthcare system, the system remains physician-centered and hospital-based. Nursing's professional potential has been largely untapped in any change efforts. Self-employed nurses have positioned themselves to deliver care based on nursing values and to promote alternative conceptions of health and healthcare. This study offers a rare exploration of this unique form of nursing practice and its potential to influence health system reform.
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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 | 0.000 | 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".