Productive Complications: Emergent Ideas in Team Communication and Patient Safety
Bibliographic record
Abstract
Communication is recognized as one of the central factors underpinning safe, high-quality teamwork in complex systems. Without effective communication, competent individuals form an incompetent team. Healthcare, traditionally predicated on the excellence and autonomy of the individual practitioner, has been somewhat slow to embrace this reality. It is only recently that we have recognized that both technical and communicative expertise are necessary for safe care. The past decade has seen important advancements in our attitudes and knowledge regarding team communication. There is increasing evidence of an association between effective team communication and valued clinical outcomes (Alfredsdottir et al. 2007; Gawande et al. 2003; Mazzocco et al. 2009; Neilly et al. 2010; Nurok et al. 2011). Research in this domain has developed a knowledge base sufficient to drive international change initiatives, such as the World Health Organization’s Safe Surgery campaign (WHO 2010). Team communication is becoming a standard component of health professional education, recognized in competency frameworks (Royal College of Physicians and Surgeons of Canada 2005) and supported by a catalogue of validated measurement tools to track trainee performance (Mishra 2009; Yule et al. 2008). Unquestionably, great strides have been made in what might be called the “first generation” of research regarding team communication and patient safety. However, some of the messier, murkier aspects of team communication remain poorly explored. In fact, one of the hallmarks of the first generation of team communication research is arguably an oversimplification of what is, at its essence, a highly complex phenomenon. Oversimplification may be a natural consequence of our efforts to make early headway in the face of a complex social phenomenon. However, the major contribution of the “second generation” of team communication research will be to build on these starting points through productive complications of what we already know. In what follows, three promising areas of study are sketched: the meaning of silence, the uptake of communication innovations and the phenomenon of intertextuality.
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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.066 |
| Scholarly communication | 0.017 | 0.031 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".