Inaugural HealthAccord Conference (SportAccord Convention, Bangkok, Thailand): The Power of Sport — The Power to Change
Bibliographic record
Abstract
SportAccord organized the inaugural HealthAccord conference on April 19, 2018, in Bangkok, Thailand. The goal of HealthAccord is for the International Sport Federations (IF) and sport industry leaders to address high-priority issues facing sport through a serious commitment to innovation to protect athlete health, to enhance athlete performance, and to stimulate action to improve global health through the promotion of physical activity. The first HeathAccord conference was organized by drawing on the knowledge and experience of experts from global health programs focused on athletes and global citizens, respectively. The first session, "The Power of Sport," addressed the application of "state of the art" sport science and sport medicine for the protection of athlete health and to enhance sport performance. "The Power of Sport" session concentrated on enabling athletes to perform spectacular feats that are "higher, stronger, faster" intended to engage and thrill global audiences without resorting to prohibited substances and methods, to enable athletes to remain active in sport for a longer career, and to increase the attraction of sport for sponsors. In the second session, "The Power to Change," sport was viewed as having an important role in promoting physical activity within their respective federations, community, and internationally. The Olympic movement, IF, and other sport stakeholders are urgently needed to become the social drivers to correct the mismatch between physical activity for health development and draw toward sedentary lifestyles of the modern world. Key outcomes of this first HealthAccord conference were the agreement among participants to develop an innovative and high-impact collaboration between IF and related stakeholders; to use sport as a social movement platform to measurably improve health, both for athletes and for global citizens.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.061 | 0.014 |
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".