Understanding the Structure of Autobiographical Memories: A Study of Trauma Memories from the 1994 Rwandan genocide
Bibliographic record
Abstract
How do we remember traumatic events, and are these memories different in individuals who experience post-traumatic stress? Some evidence suggests that traumatic events are mnemonically enhanced, or include more episodic detail, relative to other types of memories. Simultaneously, individuals with PTSD have more non-episodic details in all of their memories, a pattern hypothesized to result from impairment in executive function. Here, we explore these questions in a unique population that experienced severely traumatic events more than 20 years ago – individuals who lived through the 1994 Genocide in Rwanda. Participants recalled events from the genocide, negative events unrelated to the genocide, neutral events, and positive events. We used the Autobiographical Interview Method to label memory details as episodic or non-episodic. We found that memories from the genocide showed robust mnemonic enhancement, with more episodic than non-episodic details, and contained more details overall than any other memory type. This pattern was not impacted by post-traumatic stress. Overall, this study provides evidence that traumatic events create vivid long-lasting episodic memories, in this case even more than 20 years later.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".