The GFIT Scale: Measuring Goals Following Interpersonal Transgressions
Why this work is in the frame
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Bibliographic record
Abstract
In two studies, we created and validated a scale assessing 12 possible goals that individuals might wish to pursue when transgressed against by another person (e.g., relationship maintenance, power over the offender, retributive justice). Results demonstrated that the 12 subscales of the Goals Following Interpersonal Transgressions scale (GFIT) were reliable and exhibited convergent and discriminant validity with transgression-related interpersonal motivations (i.e., the TRIM), and relevant personality traits (i.e., the Dark Triad). Additional analyses revealed that the structure of the scale was robust across different kinds of transgressions and for differing relationships between victim and offender. We argue that the GFIT is a versatile scale with several advantages over existing measures.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it