A factor analytic and psychometric examination of pathology of separation–individuation
Bibliographic record
Abstract
Two studies are described that attempt to determine if standard-scale-reduction techniques could yield a construct-valid diagnostic screen of pathology of separation-individuation for use in nonclinical university settings. In Study 1 (N = 210), a measure of pathology of separation-individuation (PATHSEP) was reduced successfully to a single, internally consistent factor, accounting for 36% of the variance. In Study 2 (N = 304), these items also coalesced around a single factor, accounting for 35% of the variance. Study 2 also showed that PATHSEP is correlated moderately and positively with indices of insecure attachment, with the Center for Epidemiological Studies-Depression Scale, and with indices of psychiatric symptomatology (Hopkins Symptom Checklist). PATHSEP also was associated with a poorer profile of adjustment to college. Males reported more pathology of separation-individuation than did females. Evidence supports the construct validity of a shortened version of PATHSEP. Directions for future research are noted.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".