Achievement Goals in Sport: A Critique of Conceptual and Measurement Issues
Bibliographic record
Abstract
This article presents a critical analysis of the conceptualization and measurement of achievement goals in sport. It highlights conceptual and measurement inconsistencies of Nicholls’s (1984) achievement-goal theory in education with respect to its applicability to sport. It proposes that differentiation between ability and effort does not underpin the activation of task and ego goal perspectives in a sport performance context and that the definitions of task and ego involvement in the classroom might not generalize to sport. It offers an alternative conceptual approach incorporating three goal perspectives, as both a theoretical and a practical solution. It addresses goal involvement in sport performance contexts by emphasizing the value of assessing self-referent and normative conceptions of achievement at different time frames. Overall, this critique attempts to advance our understanding of both achievement goals and individual performers in the competitive sport domain.
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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 | 0.081 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.003 | 0.077 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.006 | 0.019 |
| 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".