System approach to games and competitive playing: Reply to Lebed (2006)
Bibliographic record
Abstract
Abstract In this article, we respond to some criticisms by Lebed (2006) of our previous research (McGarry, Anderson, Wallace, Hughes, & Franks, 2002) in which we reported that (a) the space–time interactions of players in sports (squash) contests might usefully be considered as a dynamical system, (b) that the other racket sports of tennis and badminton might likewise subscribe to a similar description, and (c) that doubles‐play in these same racket sports might further be explained using the same self‐organizing principles. From there, we speculated that team sports (taking soccer as an example) might ultimately also subscribe to similar principles, thus offering the possibility of a common underpinning for the space–time movements of sports players that seemingly give rise to patterned behaviours that are nonetheless unique. Lebed (2006) criticized this interpretation of sports (squash) contests as a dynamical system and instead offered a different account, though unfortunately these criticisms are inaccurate and unfounded. The most important point overlooked by Lebed (2006), and thus reiterated here, is that the essentials for a dynamical system – namely, the presence of coupled oscillators that comprise the system, as well as the sharing of information among the coupled oscillators that produces the patterned formations – are present in the racket sports for both singles‐play and doubles‐play. The presence of these essentials for team sports, however, must remain a matter of speculation for the time being as noted previously (McGarry et al., 2002).
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".