Examining the dimensions of schizotypy from the top down: A hierarchical comparison of item-level factor solutions.
Bibliographic record
Abstract
Numerous factor analytic studies of the Schizotypal Personality Questionnaire have supported a range of solutions, many with differing numbers of factors. Although some solutions have received more support than others, it remains unclear how clinicians and researchers may evaluate solutions with similar levels of empirical support in relation to one another, and few item-level analyses have been conducted. In the current study, we seek to explore the relationships among various factor solutions in a hierarchical manner using Goldberg's (2006) Bass-Ackward approach. A final sample of 847 undergraduate students completed the Schizotypal Personality Questionnaire with a Likert-style response format. Item-level exploratory factor analyses with between one and nine factors were extracted. Interrelationships among these solutions were examined. Each solution was evaluated in terms of its content, statistical significance, simple structure, and consistency with previous findings. Factor solutions at several levels were found to replicate findings from past factor analyses in terms of individual factor content and relative merit. Solutions with between four and six factors received the most support and solutions with up to seven factors were found to achieve support. (PsycINFO Database Record
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".