Hidden Stories, Toxic Stories, Healing Stories: The Power of Narrative in Peace and Reconciliation
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
Research on narrative is more than simply listening to (more or less) nice stories. There are stories that are hidden between the lines; these need to be noticed and retrieved. There are stories that can be toxic to be exposed to; these need to be coped with and conceived. But there may be stories that have a healing quality, too—stories that can contribute to peace and reconciliation. These three possible qualities of narratives are the focus of the following paper, which was delivered in October 2008, at the launch of the Centre for Interdisciplinary Research on Narrative at St. Thomas University in Fredericton, New Brunswick, Canada. The lecture was based on his interdisciplinary research project Geschichte und Erinnerung [History and Memory, www.geschichte-erinnerung.de] in which interviews with Nazi followers, bystanders, and perpetrators were conducted and analysed. Marks presented one of the key findings of this research—shame—and its effect on what the interviewees recounted, as well as its relevance for National Socialism and present-day German society.
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) | 0.000 | 0.000 |
| 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) | 0.001 | 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