<scp>CENTRE</scp> : creating psychological safety in groups
Bibliographic record
Abstract
BACKGROUND: Ten years of clinical and teaching experience has shown us that when teams or groups come together, it is often for a commonly understood and agreed upon purpose, but often without an agreed upon process of how to work together. Explicit guidelines in this regard promote psychological safety. CONTEXT: This article presents a method of developing agreements that can be used in a variety of settings to create psychological safety and cohesion. In our experience, agreements about how people join together seem to be developed implicitly. Assumption-based and implicit agreements can engender friction because unspoken or unclear agreements are not easily addressed because they are not universally understood. INNOVATION: A literature review helped to identify key factors contributing to psychological safety and led to creating 'CENTRE' to help clinical teams apply these factors. We are now starting to evaluate its impact. We believe a tool such as CENTRE facilitates the development of explicitly articulated group formation and maintenance guidelines, thus reducing the risk of interpersonal discord. IMPLICATIONS: We propose that a tool such as CENTRE be considered for a range of group situations, including clinical family meetings, teaching, professional teams and Balint-type groups. We are currently using this approach in clinical, academic and other professional environments. Findings from a survey of groups where CENTRE was used suggested that participants find the process useful. We believe a tool such as CENTRE can be used to help address relational issues, promote psychological safety, inclusion and trust among members, and reduce the risk of undeclared expectations and assumptions from dictating how groups function. Assumption-based and implicit agreements can engender friction because unspoken or unclear agreements are not easily addressed.
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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 | 0.018 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.011 |
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".