Reactions to the symposium: Effectiveness of the group-mediated cognitive behavioural intervention
Bibliographic record
Abstract
As symposium discussant, Dr. Eys will first comment on the group nature of the GMCB intervention. Does it truly differ from other interventions whose participants take part in physical activity (PA) that is led by an instructor? Could the GMCB group effect amount to simple social support or nonspecific effects of participating together with others? Second, he will offer possible indicators or measures that need to be examined in order to confirm that the group has a unique identity of sufficient strength to confirm the group is an agent of change (e.g., cohesion). Third, he will remark on his impressions of the relative effectiveness of the GMCB, its strengths, and limitations based upon the evidence presented in the symposium. Do participants really depend on the group and do they transition well from the group to self-managed PA? Finally, he will suggest other settings in which the GMCB intervention model might be employed to promote increased PA (e.g., the worksite) and the related knowledge translation challenges that may arise in such new contexts.Acknowledgments: Supported by SSHRC Canada Research Chair Funding
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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 | 0.029 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".