“If you love something that much, you're willing to get through the obstacles”: A grounded theory of grit in competitive sport
Bibliographic record
Abstract
In order to achieve success, competitive athletes are required to meet the extensive demands and overcome the numerous obstacles that are associated with their sporting careers. The construct of grit—characterized by passion and perseverance over extended periods of time—has been associated with goal achievement in sport psychology research. However, the advancement of this field has been hindered by a lack of sufficient theory. The purpose of this study was to construct a grounded theory of competitive athletes’ grit in sport using constructivist grounded theory methodology. Twenty-eight adult participants (15 women, 13 men; Mage = 27.3 years, SD = 8.2; 22 athletes, 5 coaches, 1 sport parent) involved in competitive sport participated in one-on-one semi-structured interviews. In total, 1933 minutes of audio was recorded. Data analysis followed an iterative process of initial coding, focused coding, axial coding, and theoretical integration. The constructed grounded theory suggests that grit was conceptualized as a malleable dispositional tendency formed over time as athletes amassed various positive and setback experiences in sport. With the encouragement of supportive others, athletes would adopt adaptive cognitions about success and failure in sport. These cognitions would then develop into a propensity to identify and strive towards personally meaningful long-term goals in sport. Grit was understood to lead to several outcomes; including sport-specific goal achievement, athlete thriving, and athlete languishing. This study contributes to the broader understanding of the underlying mechanisms that encapsulate competitive athletes’ sport-specific grit and offers implications for practitioners and sport researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.029 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".