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
Understanding firm responses to breaches of trust is critical to managing relationships between firms and stakeholders. Although forgiveness is a vital link in the trust-repair process, there is so far no article that examines forgiveness research to identify factors that should influence the propensity of top managers of a transgressed firm to forgive a transgressing stakeholder. This article fills that void by integrating concepts of trust restoration, forgiveness, stakeholder culture, and transgressor power to develop a model that predicts the level of forgiveness a firm is likely to extend to a stakeholder that has breached the firm’s trust. The visibility and magnitude of a transgression—as well as transgressor intentions, reactions, history, reputation, and power—influence the firm’s response, within the context of its stakeholder culture. Our model can help managers, consultants, and investors anticipate and interpret transgressed firm reactions to a transgressing stakeholder’s breach of trust, with implications for relations with the transgressor, relations with other stakeholders, and future firm performance.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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