Consideration of future consequences: Relationships with self-regulated learning, deliberate practice and skill level in individual sports
Bibliographic record
Abstract
Consideration of Future Consequences (CFC) is the extent that people consider the future outcomes of current behaviours (Joireman et al., 2006). It may differentiate athletes' dispositions to self-regulate and enhance amounts of sport practice (Barone et al., 1997). This study explored whether CFC had a bearing on relationships between self-regulated learning (SRL), deliberate practice (DP), and acquired skill. 272 North American individual sport athletes ranging from local to international level (196 male; Mage = 22.48, range 18-35; MDP = 12.95 weekly hrs, SD = 6.47) completed the SRL-SRS for Sport Training (Bartulovic et al., 2017), the CFC-14 (CFC-Future, CFC-Immediate; Joireman et al., 2012), and reported weekly DP amounts. A MANOVA tested differences in CFC-F and CFC-I between recreationally competitive, less-elite and elite groups. Results showed no differences (ps > .09). Second, correlational analyses showed no associations between CFC-F (r = -.05, p = .39) or CFC-I (r = .11, p = .06) with DP. To further explore whether associations between SRL and DP depended on CFC, CFC-I and CFC-F were each tested as a moderator; results showed no moderating effects (ps > .14). There were notable correlations (ps < .01) between CFC-F and overall self-regulation (r = .35), and each of six constituent SRL-SRS processes (.21 to .27). CFC-I correlated with four SRL processes (-.14 to -.17). Discussion focuses on CFC-F as an antecedent to SRL-SRS rather than a moderator of associations between SRL and DP, as well as the future role of CFC in sport expertise research.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".