Dissociative complexity: Antecedents and clinical correlates of a new construct.
Bibliographic record
Abstract
OBJECTIVE: To the extent that dissociation is a multidimensional phenomenon, and given a growing literature on complex posttraumatic outcomes, we hypothesized a new construct: dissociative complexity (DC). DC is defined as the tendency to simultaneously endorse multiple, relatively independent dissociative dimensions into their clinical ranges, and therefore represents the overall breadth or complexity of an individual's dissociative response. METHOD: DC was evaluated in general population and prison participants using the Multiscale Dissociation Inventory (MDI; Briere, 2002). RESULTS: DC was higher among prisoners and women, and, as hypothesized, was associated with cumulative trauma and serious comorbidities (suicidality and substance abuse), even when controlling for generally elevated dissociation. CONCLUSIONS: DC appears to be a meaningful clinical construct that is phenomenologically and empirically different from a unidimensional index of dissociative severity. DC may serve as a clinical marker for multiple trauma exposures, complex dissociative outcomes, and risk of problematic comorbidities. (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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".