Lefthanders advantages in handball - Negative frequency effects depend on familarity of throwing patterns
Bibliographic record
Abstract
The emergence of a lefties’ advantage in interactive sports can best be explained by negative frequency-dependent effects (Hagemann, 2009) assuming that the greater frequency of situations with right-handed opponents makes it possible to discriminate and predict a right-handed opponent’s movement more precisely. A study by Schorer, Baker, Fath & Jaitner (2007) demonstrated that expert players are capable of using strategically varying movement patterns in contrast to advanced players who use stable movement patterns. Novices, however, show a high variability in their movement patterns. The aim of our study was to test whether negative frequency-dependent effects occur only against advanced players and not versus experts or novices. Video stimuli were taken from a study of Schorer and colleagues (2007). To receive videos of the same quality of right- and left-handed throwers, videos were flipped vertically. The video sequences were presented to three participant groups (goalkeepers performing on a national level of competition, on a regional level of competition and p.e. students) on a computer screen and participants were instructed to predict the direction of the throw. We conducted a four factorial analysis of variance design with expertise of goalkeepers (experts, advanced, and novice goalkeepers) as between-subject and expertise of throwers (experts, advanced, and novice thrower), temporal occlusion conditions and laterality of presented throwers as within-subject factors. Results indicated the expected differences between left- and right-handed presented throwers as well as its interaction with various other factors. Results indicate that negative frequency effects depend on viewer’s familiarity with the throwing patterns displayed.Acknowledgments: Hagemann, N. (2009). The advantage of being left-handed in interactive sports. Attention, Perception & Psychophysics, 71, 1641-1648. Schorer, J., Baker, J., Fath, F. & Jaitner, T. (2007). Identification of interindividual and intraindividual movement patterns in handball players of varying expertise levels. Journal of motor behavior, 39(5), 409-421.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".