Linguistic Measurement Invariance and Stability-Equivalence of the Personality Inventory for <i>DSM-5</i> Among Bilingual Participants
Bibliographic record
Abstract
The linguistic equivalence of the Personality Inventory for DSM-5 (PID-5) has never been investigated using a within-subject design, that is, among bilingual individuals. Also, the stability-equivalence of the PID-5 using two linguistic versions is unknown. Thus, this within-subject, test-retest study aims at (a) establishing the measurement invariance of the PID-5 among bilinguals, and (b) providing indices of stability-equivalence using distinct versions with tight confidence intervals. Data from a sample of bilingual participants (N = 605), who were administered the PID-5 over a 1-2-week interval in French and English, were utilized. The PID-5 reached the (full) strong invariance level using longitudinal invariance analyses, indicating that the PID-5 structure is the same and that scores are interchangeable, while controlling for sampling confounds. The indices of stability-equivalence were high across traits. The PID-5 yields scores reflective of genuine differences, at least at the domain level, providing solid ground to study personality across societies.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".