Four Decades of Group Hypnosis Scales: What Does Item-Response Theory Tell Us About What We?ve Been Measuring?
Bibliographic record
Abstract
To overcome problems with previous psychometric approaches to hypnosis scales, the authors applied full-information factor analysis, based on multidimensional item-response theory (IRT), to a 39-year sample of 11,517 records of the Harvard Group Scale of Hypnotic Susceptibility, Form A (HGSHS:A). They also performed a comparable analysis on the standardization sample of the Waterloo-Stanford Group C Scale (WSGC). The HGSHS:A emerges as two-factored, whereas the WSGC more closely approaches unidimensionality. The HGSHS:A factor structure and means show very little change over 4 decades. However, IRT-based item analysis on the HGSHS:A indicates that problems such as "pseudoguessing" on 2 items limit the quality of the item set. The authors propose alternative substantive interpretations of the traits that may underlie the two-factor structure.
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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 | 0.045 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".