Silence, power and communication in the operating room
Bibliographic record
Abstract
Abstract Title. Silence, power and communication in the operating room. Aim. This paper is a report of a study conducted to explore whether a 1‐ to 3‐minute preoperative interprofessional team briefing with a structured checklist was an effective way to support communication in the operating room. Background. Previous research suggests that nurses often feel constrained in their ability to communicate with physicians. Previous research on silence and power suggests that silence is not only a reflection of powerlessness or passivity, and that silence and speech are not opposites, but closely interrelated. Methods. We conducted a retrospective study of silences observed in communication between nurses and surgeons in a multi‐site observational study of interprofessional communication in the operating room. Over 700 surgical procedures were observed from 2005–2007. Instances of communication characterized by unresolved or unarticulated issues were identified in field notes and analysed from a critical ethnography perspective. Findings. We identified three forms of recurring ‘silences’: absence of communication; not responding to queries or requests; and speaking quietly. These silences may be defensive or strategic, and they may be influenced by larger institutional and structural power dynamics as well as by the immediate situational context. Conclusions. There is no single answer to the question of why ‘nobody said anything’. Exploring silences in relation to power suggests that there are multiple and complex ways that constrained communication is produced in the operating room, which are essential to understand in order to improve interprofessional communication and collaboration.
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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".