Living in History in Lebanon: The influence of chronic social upheaval on the organisation of autobiographical memories
Bibliographic record
Abstract
The Living in History (LiH) effect is a litmus test for the degree to which historical events reorganise autobiographical memory. The LiH effect was studied in two Lebanese samples: a Beiruti sample that lived in the epicentre of the 15-year Lebanese Civil War (1975-1990) and another group from the Bi'qa region who lived in an area that was indirectly exposed for most of the civil war but experienced one short-term period of war during the Israeli invasion. Using the two-phase word-cueing task to elicit dated autobiographical memories, we observed a significantly stronger LiH effect in the Beirut sample but also a significant yet weaker LiH effect in the Bi'qa sample. In addition to the main finding we offer evidence that the LiH effect waxes and wanes with the level of conflict in an area and that reported personal experiences of war exposure predict the strength of the LiH effect. Our findings suggest that collective transitional events which produce a marked change in the fabric of daily living engender historically defined autobiographical periods which give structure and organisation to how individuals remember their past.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".