The Validity and Utility of the Positive Presentation Management and Negative Presentation Management Scales for the Revised NEO Personality Inventory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Schinka, Kinder, and Kremer developed "validity" scales for the Revised NEO Personality Inventory (NEO PI-R; Costa & McCrae) to detect underreporting-the Positive Presentation Management (PPM) Scale and overreporting-the Negative Presentation Management (NPM) Scale. In this investigation, the clinical utility of these scales was examined using the established validity scales from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2; Butcher et al.) as the referent. The sample was composed of 370 psychiatric patients who completed the NEO PI-R and the MMPI-2 as part of a routine evaluation. Results indicated that response distortion compromised the utility of the NEO PI-R domain scales. Moreover, the PPM and NPM scales and an NPM-PPM index significantly differentiated invalid under-and overreporting groups from a valid responding group. The PPM and NPM-PPM index were adequate in classifying under- and overreporters, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it