Does Love Influence Athletic Performance? The Perspectives of Olympic Athletes
Bibliographic record
Abstract
In this brief report, we provide an initial account of the association between love and athletic performance from the perspective of Olympic athletes. We posit that Romantic Passionate Love (RPL) and athletic performance may both involve the reward-motivation system of the brain. Based on this premise, we explored whether activation in one domain (love) might influence the other (sport). Our investigation was framed using Sternberg's triangular theory of love. Twenty Olympic athletes representing different sports were interviewed at the Games. Most athletes (n = 15) reported that their performance was better while in love; however, qualitative responses suggested that the benefits were correlated with rather than resulting from RPL. Although the athletes were provided with a definition of RPL and affirmed that their relationship met the criteria, interview responses reflected companionate rather than passionate love, suggesting that RPL may be differentially conceptualized across cultures. The study provides preliminary data that may be used to inform and refine future work on this topic.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".