Choking Susceptibility and the Big Five Personality Traits
Bibliographic record
Abstract
Background: Choking susceptibility is the likelihood or potential of an individual choking under pressure. Choking susceptibility can be influenced by personality traits. Objective: The purpose of this study is to examine the differences between the Big Five personality traits on choking susceptible and choking non-susceptible individuals from a Canadian University using a cross-sectional design. It was hypothesized that choking susceptibility could be predicted by the Big Five personality traits. Methods: A protocol developed by Mesagno and colleagues, comprising a self-consciousness scale, sports anxiety scale, and coping style scale, was used to measure choking susceptibility. The protocol has only been used within athlete populations. This study is the first to use the choking susceptibility protocol outside of sports, specifically for undergraduate students (N = 177). Results: A logistic regression revealed that the personality traits could significantly predict choking susceptibility. Neuroticism was the sole significant predictor. Higher neuroticism values significantly increased the probability of an individual choking susceptible. Conclusion: According to the current study, neuroticism predicted choking susceptibility. Future research should address choking susceptibility in different contexts and more closely examine the relationship between choking susceptibility and actually choking under pressure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".