Consensus group sessions are useful to reconcile stakeholders’ perspectives about network performance evaluation
Bibliographic record
Abstract
BACKGROUND: Having a common vision among network stakeholders is an important ingredient to developing a performance evaluation process. Consensus methods may be a viable means to reconcile the perceptions of different stakeholders about the dimensions to include in a performance evaluation framework. OBJECTIVES: To determine whether individual organizations within traumatic brain injury (TBI) networks differ in perceptions about the importance of performance dimensions for the evaluation of TBI networks and to explore the extent to which group consensus sessions could reconcile these perceptions. METHODS: We used TRIAGE, a consensus technique that combines an individual and a group data collection phase to explore the perceptions of network stakeholders and to reach a consensus within structured group discussions. RESULTS: One hundred and thirty-nine professionals from 43 organizations within eight TBI networks participated in the individual data collection; 62 professionals from these same organisations contributed to the group data collection. The extent of consensus based on questionnaire results (e.g. individual data collection) was low, however, 100% agreement was obtained for each network during the consensus group sessions. The median importance scores and mean ranks attributed to the dimensions by individuals compared to groups did not differ greatly. Group discussions were found useful in understanding the reasons motivating the scoring, for resolving differences among participants, and for harmonizing their values. CONCLUSION: Group discussions, as part of a consensus technique, appear to be a useful process to reconcile diverging perceptions of network performance among stakeholders.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 teacher head, 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".