Conceptualizing forgiveness: A review and path forward
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
Summary Forgiveness is a valuable conflict management strategy that has numerous benefits in workplace settings (e.g., for employees, team dynamics, dyadic relationships, and organizations). However, important conceptual questions have emerged, especially as scholars have begun to examine forgiveness in the workplace. To better understand these issues, we conduct a critical review and analysis of the extant literature to identify key conceptual issues that are creating challenges for the study of forgiveness in organizational behavior. Building on these insights, we propose that conceptualizing forgiveness as a special case of emotion regulation can provide a strong conceptual and theoretical foundation that can address these challenges. Moreover, we outline how this approach can create exciting new research avenues that can enhance our theoretical understanding of forgiveness (e.g., distinguishing between the processes underlying forgiveness; identifying points of intervention to promote forgiveness; exploring the role of time in forgiveness; examining how context impacts forgiveness). We also identify how this approach can provide novel practical insights into how forgiveness can be facilitated and effectively managed in the workplace.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.023 | 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