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
Abstract. Consensus is emerging that the constellation of dark personalities should include the sadistic personality. To build a four-factor measure, we modified and extended the Short Dark Triad (SD3) measure to include sadism. A series of three studies yielded the Short Dark Tetrad (SD4), a four subscale inventory with 7 items per construct. Study 1 ( N = 868) applied exploratory factor analysis (EFA) to a diverse 48-item pool using data collected on MTurk. A 4-factor solution revealed a separate sadism factor, as well as a shifted Dark Triad. Study 2 ( N = 999 students) applied EFA to a reduced 37-item set. Associations with adjustment and sex drive provided insight into unique personality dynamics of the four constructs. In Study 3 ( N = 660), a confirmatory factor analysis (CFA) of the final 28 items showed acceptable fit for a four-factor solution. Moreover, the resulting 7-item subscales each showed coherent links with the Big Five and adjustment. In sum, the four-factor structure replicated across student and community samples. Although they overlap to a moderate degree, the four subscales show distinctive correlates – even with a control for acquiescence. We also uncovered a novel link between sadism and sexuality, but no association with maladjustment.
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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it