A conceptual framework contributing to nursing administration and research
Bibliographic record
Abstract
The health care system has undergone major changes in the last decade. With greater acuity and complexity of illness, the adoption of innovative technologies and the shortage of health care personnel, the coordination and integration of health care services has become increasingly demanding for administrators. Growing dissatisfaction and concerns about safety issues are being expressed by the users of care who need to navigate through an increasingly complex system and by health care personnel who feel less efficient within the organization. Nursing administrators have a responsibility to address these issues but there is little scientific evidence to guide their actions. There are also few comprehensive models highlighting the main components of nursing administration - models that could guide nursing administration research. This paper presents a conceptual framework for nursing administration and research that links patient health care needs, nursing resources and the nursing care processes to the context of the health care system, and the social, political and cultural environments of care. A selected review of the oncology and cancer care literature is presented to demonstrate how this framework can organize existing knowledge about these concepts in the context of cancer care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.007 | 0.047 |
| Scholarly communication | 0.020 | 0.020 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".