The COVID-19 pandemic as autobiographical period: evidence from an event dating study
Bibliographic record
Abstract
The COVID-19 Pandemic is undoubtedly one of the most impactful and ubiquitous public events in recent history. In this study, we focused on how it affected the organisation of autobiographical memory by examining how often individuals referred to the COVID-19 Pandemic while estimating the date of their autobiographical memories. To that end, we collected word-cued memories from the recent past, event dating protocols, COVID-relatedness ratings, and the transitional impact scores from first-year undergraduates. We found that participants frequently recalled COVID-related memories, and often used the Pandemic as a temporal landmark for dating both COVID-related and unrelated memories. Importantly, reference to the Pandemic in dating estimates was as frequent as the references to other important life periods (high school, university). Despite affecting the lives of these individuals only moderately in psychological and material terms, these data indicate that the Pandemic has become a prominent landmark in autobiographical memory, shaping the way we remember and situate past experiences.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".