Intersections of power: videoconferenced debriefing of a rural interprofessional simulation team by an urban interprofessional debriefing team
Bibliographic record
Abstract
INTRODUCTION: Simulation as an educational tool is known to have benefits. Moreover, the use of simulation in continuing interprofessional development is vital in rural and remote communities with limited case volumes and resources. This study explored power dynamics between rural simulation participants and urban expert co-debriefers during a simulated operating room crisis and debriefing. The aim is to gain a rich understanding of rural/urban relational dynamics embedded within the constraints and affordances of videoconferencing technology. METHODS: In situ observations of a videoconference-enabled simulation and debriefing were conducted, followed by seven semi-structured interviews, in this qualitative case study. A sociomateriality lens with additional sensitizing concepts of power from critical theory was employed to explore human and nonhuman interactions between rural learners, urban co-debriefers, and videoconferencing technology. RESULTS: The interviews exposed subtle expressions of power dynamics at play that were curiously not observable in the enactment of the exercise. Rural learners appreciated the objectivity of the urban debriefers as well as the nurse/physician dyad. However, rural participants appeared to quietly dismiss feedback when it was incongruent with their context. Videoconference technology added both benefits and constraints to these relational dynamics. DISCUSSION: Awareness of power relationships, and insights into affordances and constraints of videoconferencing may enhance operationalization of interprofessional simulation-based education (SBE) in rural and remote contexts.
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 | 0.004 | 0.017 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".