Verificação de propriedades psicométricas do Inventário de Cristalização das Preferências Profissionais
Bibliographic record
Abstract
Psychometric Properties of the Professional Preferences Crystallization Inventory The Professional Preferences Crystallization Inventory (PPCI) is an important instrument which evaluates two dimensions: choosing a career and thus promoting professional development. This study presents the steps of the elaboration of the PPCI and the measurement of its psychometric properties obtained with a sample of 487 students from a private university in the south of Brazil, of both sexes and age ranging from 17 and 51 ( X = 22; X 5% = 21,3; Median = 20; Mode = 19). The results are presented systematically according to its theoretically proposed dimensions. Alpha coefficients for the two dimensions studied are found to be highly satisfactory (α > 0,85). The results of both the factor analysis and correlations (item-item, item-dimension, and item-total scale) seem to support a two-factor solution. Further studies are still needed to proceed with the investigation of other important psychometric qualities.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.005 | 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".