Sync or separate? No compelling evidence for unintentional interpersonal coordination between Usain Bolt and Tyson Gay on the 100-meter world record race.
Bibliographic record
Abstract
; Varlet & Richardson, 2015) the 100-m sprint final of the World Championship in Athletics in Berlin of 2009 (i.e., the current world record race) was analyzed. That study reported occurrence of spontaneous, unintentional interpersonal synchronization between Usain Bolt and Tyson Gay, the respective winner and runner-up of that race. In the present commentary article, however, we argue that the results and conclusion of that study cannot be warranted because of methodological shortcomings. We addressed the same research question and reassessed the same race using an alternative data analysis method. These results revealed that as yet there is no sufficient ground to conclude that in the 100-m world record race synchronization occurred between Bolt and Gay. Yet, our reanalysis suggested that even at this very elite level the individual movement frequencies did seem to vary to such an extent that synchronization would theoretically still be possible, thereby providing incentives for further examination of potential unintentional synchronization in coactive sports. (PsycINFO Database Record
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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".