Contextual influences on baseball ball-strike decisions in umpires, players, and controls
Bibliographic record
Abstract
Baseball umpires, players, and control participants with no baseball experience were asked to call balls and strikes for video clips. In a basic judgement task, umpires and players were significantly better at calling pitches than controls. In a direct information task, borderline pitches were presented following clips of definite balls and definite strikes. Participants called target pitches closer to the strike end of the scale when viewed after definite balls than when they followed definite strikes. Similarly, when borderline pitches were shown in different pitch counts, participants called pitches more towards the strike end of the scale when there were three balls in the count (3-0, 3-2). These findings indicate that the standard for evaluation changes based on the context in which stimuli are processed. Moreover, the strength of the contextual factors is illustrated in that the effects were shown in observers with and without experience in the task. Overall, however, umpires had a greater tendency to call strikes, indicating that they may use a norm of "hastening the game".
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".