Influencing and Impacting the Profession Through Governance Opportunities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In addition to board leadership of health care organizations and corporations, there are strategic opportunities for nurses to participate in professional association boards and commissions and expert panels. These boards have specific and unique challenges and opportunities, and it is important for nurse leaders to serve in shaping the direction of the profession. Nursing as a profession has an opening to solve many of the care delivery issues that face the country. A strategic contribution to association boards and commissions can influence the health care delivery system changes needed to improve quality of care, access to care, and reducing costs. This article describes similarities and differences of service on association boards and commissions compared with organizational and corporate boards. Through these leadership roles, the larger community can observe influential nurses in an essential role. These leadership opportunities, including membership boards, commissions, and content expert panels, call for a special understanding of those governance structures and the contributions that nurse leaders can make to impact health care. Association and membership organizations have undergone many changes in the past 10 years, and new models of governance and leadership have been called into play. There are challenges and opportunities in serving on these boards and commissions. Maximizing the leadership and governance roles of this type of service is a critical contribution that nurses can make to impact the profession of nursing and the greater health care system.
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.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it