Examination of Measures of Perfectionism for Structural and Measurement Invariance in an Italian and a Canadian Sample
Bibliographic record
Abstract
Perfectionism measures developed in English-speaking populations have become frequently used in many non-English contexts, including in Italy. Establishing structural and measurement equivalence of instruments between Canadian and Italian samples is therefore important in establishing the validity of these concepts and instruments in Italian contexts, and to allow for direct cross-cultural comparisons. The current study investigated the measurement equivalence between a Canadian and an Italian sample for the commonly used measures of perfectionism constructs based on the Comprehensive Model of Perfectionistic Behavior. The Hewitt & Flett Multidimensional Perfectionism Scale, the Perfectionistic Self-Presentation Scale, and the Perfectionism Cognitions Inventory were examined for configural, metric, and scalar invariance via equivalence testing of multigroup confirmatory factor analysis models. The results showed some evidence for configural and metric equivalence for the three measures, thus facilitating cross-cultural interpretation of pattern of associations. However, there was no consistent evidence for scalar invariance, thus suggesting that direct comparisons of perfectionism levels between the two contexts cannot be meaningfully interpreted. This highlights the need for research in both Canadian and Italian contexts to understand cross-cultural differences and similarities in perfectionism.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".