Bibliographic record
Abstract
Forgiveness has traditionally been characterized an affective response to a wrongdoing, i.e., a psychological process that involves ridding oneself of resentment or other negative reactive attitudes. In contrast to the prevailing model, this paper advocates for the emerging position that forgiveness should be understood as a normative power akin to a promise. In particular, I argue that forgiveness involves surrendering the right to discount the interests of a perpetrator (a special permission the victim acquires in virtue of having been wronged). I argue that this model fits and/or explains important features of forgiveness, such as the idea that forgiveness is a personal response to a blameworthy wrong, that forgiveness re-establishes a relation of equality, and that forgiveness is "normatively significant." I further develop the position by showing how it can provide a unified case of paradigmatic forgiveness, self-forgiveness, and third-party forgiveness—this explanatory power distinguishes the view from previous articulations of the idea that forgiveness is a normative power. The final section further explores these distinctions by delimiting the scope of forgiveness to exclude powers related to apologies, compensation, or “redemption.”
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".