Bibliographic record
Abstract
PURPOSE: Many nations are focussing on health care's Triple Aim (quality, overall community health and reduced cost) with only moderate success. Traditional leadership learning programmes have been based on a taught curriculum, but the purpose of this paper is to demonstrate more modern approaches through procedures and tools. DESIGN/METHODOLOGY/APPROACH: This study evolved from grounded and activity theory foundations (using semi-structured interviews with ten senior healthcare executives and qualitative analysis) which describe obstructions to progress. The study began with the premise that quality and affordable health care are dependent upon collaborative innovation. The growth of new leaders goes from skills to procedures and tools, and from training to development. FINDINGS: This paper makes "frugal innovation" recommendations which while not costly in a financial sense, do have practical and social implications relating to the Triple Aim. The research also revealed largely externally driven health care systems under duress suffering from leadership shortages. RESEARCH LIMITATIONS/IMPLICATIONS: The study centred primarily on one Canadian community health care services' organisation. Since healthcare provision is place-based (contextual), the findings may not be universally applicable, maybe not even to an adjacent community. PRACTICAL IMPLICATIONS: The paper dismisses outdated views of the synonymity of leadership and management, while encouraging clinicians to assume leadership roles. ORIGINALITY/VALUE: This paper demonstrates how health care leadership can be developed and sustained.
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 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 | 0.021 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".