Incremental validity evidence supporting the domain-specific conceptualization and measurement of grit in intercollegiate student-athletes
Bibliographic record
Abstract
The personality trait of grit (Duckworth, Peterson, Matthews, & Kelly, 2007) has traditionally been conceptualized and measured as a global or domain-general construct. The purpose of this study was to determine if grit is best conceptualized and measured as a domain-general construct or as a domain-specific construct (see Griffin, McDermott, McHugh, Fitzmaurice, & Weiss, 2016). To address this question, we sought incremental validity evidence to determine if domain-specific measures of grit could explain variance in domain-matched achievement-related criterion variables beyond the variance explained by a global measure of grit. A sample of 251 (102 female) intercollegiate student-athletes (M age = 20.34 years, SD = 2.0) completed three versions of Duckworth et al.'s Grit Scale: the original global (domain-general) version, a sport version, and a school version. Participants provided their Grade Point Average (GPA) and completed a self-report measure of perfectionistic strivings and perfectionistic concerns in sport (see Stoeber & Madigan, 2016). Results of a hierarchical regression analysis indicated that the school measure of grit explained an additional 20% of the variance in university GPA beyond the variance explained by the global measure of grit (p < .001). Results of a second hierarchical regression analysis indicated that the sport measure of grit explained an additional 3% of the variance in student-athletes' perfectionistic strivings in sport beyond the variance explained by the global measure of grit (p < .05). The results provide incremental validity evidence supporting the domain-specific conceptualization and measurement of grit in academic and sport settings.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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".