Redefining unforgiveness: Exploring victims’ experiences in the wake of unforgiven interpersonal transgressions
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
This study explored victims’ experiences in the aftermath of unforgiven offenses. Semi-structured interviews with 13 individuals discussing two unforgiven offenses revealed considerable variability in the experiences of unforgiveness, suggesting that unforgiveness may be more multifaceted than previously believed. In addition to the negative emotions and rumination previously posited to characterize unforgiveness, novel themes emerged describing unforgiving cognitions (e.g., the offense is unforgiveable) and construals of the offender. Participants varied along each dimension, resulting in a range of outcomes (e.g., forgiveness, lingering personal distress, finding peace without forgiving). Implications for conceptualizing unforgiveness and counseling those who struggle with unforgiven offenses are discussed.
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 | 0.000 | 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 | 0.000 |
| 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