Diagnosing and Improving Functioning in Interdisciplinary Health Care Teams
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
Interdisciplinary teams play a key role in the delivery of health care. Team functioning can positively or negatively impact the effective and efficient delivery of health care services as well as the personal well-being of group members. Additionally, teams must be able and willing to work together to achieve team goals within a climate that reflects commitment to team goals, accountability, respect, and trust. Not surprisingly, dysfunctional team functioning can limit the success of interdisciplinary health care teams. The first step in improving dysfunctional team function is to conduct an analysis based on criteria necessary for team success, and this article provides meaningful criteria for doing such an analysis. These are the following: a common team goal, the ability and willingness to work together to achieve team goals, decision making, communication, and team member relationships. High-functioning interdisciplinary teams must exhibit features of good team function in all key domains. If a team functions well in some domains and needs to improve in others, targeted strategies are described that can be used to improve team functioning.
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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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