Evaluating social media as a platform for the implementation of a team building protocol
Bibliographic record
Abstract
Over a decade ago, Brawley and Paskevich (1997) identified the need to evaluate team building (TB) interventions in activity settings. The purpose of this study was to evaluate the efficacy of Freshman Fitteen, a TB intervention delivered online to enhance group cohesion and physical performance of first year university students. Seven semi-structured focus groups were conducted with participants who completed the program (n=14), dropouts (n=5), and exercise leaders (n=5) two weeks post intervention. Participant interview questions investigated what factors participants identified that led them to complete or dropout of the program and whether the online TB protocol was effective. Interview questions for the exercise leaders centered on identifying the strengths and weaknesses of delivering a TB intervention online. Emerging themes for participant adherence included social support and cohesion. Emerging themes for participant drop out included lack of time and accessibility. In terms of the effectiveness of the online intervention, participants stated that they enjoyed the online TB experience and improved their physical activity adherence through the content that was delivered online. Exercise leaders reported that the strengths of the online TB intervention included improved communication among participants and improved accessibility to the team building content for participants and leaders. Findings are consistent with past research examining the beneficial effects of team building (Stevens & Bloom, 2003; Voight & Callaghan, 2001) and offers support for an online TB intervention to help first year university students to overcome the barriers to physical activity and improve exercise adherence.Acknowledgments: The project was supported by the Schulich School of Education, Nipissing University.
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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 | 0.101 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".