Conflicting Messages
Bibliographic record
Abstract
PURPOSE: Despite the importance of leadership in interprofessional health care teams, little is understood about how it is enacted. The literature emphasizes a collaborative approach of shared leadership, but this may be challenging for clinicians working within the traditionally hierarchical health care system. METHOD: Using case study methodology, the authors collected observation and interview data from five interprofessional health care teams working at teaching hospitals in urban Ontario, Canada. They interviewed 46 health care providers and conducted 139 hours of observation from January 2008 through June 2009. RESULTS: Although the members of the interprofessional teams agreed about the importance of collaborative leadership and discussed ways in which their teams tried to achieve it, evidence indicated that the actual enactment of collaborative leadership was a challenge. The participating physicians indicated a belief that their teams functioned nonhierarchically, but reports from the nonphysician clinicians and the authors' observation data revealed that hierarchical behaviors persisted, even from those who most vehemently denied the presence of hierarchies on their teams. CONCLUSIONS: A collaborative approach to leadership may be challenging for interprofessional teams embedded in traditional health care, education, and medical-legal systems that reinforce the idea that physicians sit at the top of the hierarchy. By openly recognizing and discussing the tensions between traditional and interprofessional discourses of collaborative leadership, it may be possible to help interprofessional teams, physicians and clinicians alike, work together more effectively.
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 | 0.009 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.201 | 0.105 |
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".