A Multi-Method Multi-Analytic Approach to Establishing Internal Construct Validity Evidence: The Sport Multidimensional Perfectionism Scale 2
Bibliographic record
Abstract
This article presents a chronology of three empirical studies that outline the measurement process by which two new subscales (Doubts about Actions and Organization) were developed and integrated into a revised version of CitationDunn, Causgrove Dunn, and Syrotuik's (2002) Sport Multidimensional Perfectionism Scale (i.e., the Sport-MPS-2). All studies were designed to provide internal validity evidence that supported the inclusion of these new subscales into the instrument. Phase 1 determined that expert judges regarded the new Doubts about Actions and Organization items (n = 12) as possessing adequate levels of content-relevance and content-representativeness. Phases 2 and 3 examined the latent dimensionality of the Sport-MPS-2 using multidimensional scaling and factor analytic techniques. At a structural level, results indicated that the new Doubts about Actions and Organization subscales were suitable for inclusion in the Sport-MPS-2. Initial external validity evidence is presented via correlational and regression analyses surrounding the relationships between Sport-MPS-2 subscales and global self-esteem. The benefits of utilizing a multi-method multi-analytic approach in the initial stages of the construct validation process are discussed.
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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 | 0.153 | 0.243 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".