The Blursday Database: Individuals' Temporalities in Covid Times
Bibliographic record
Abstract
Abstract The Covid-19 pandemic and associated lockdowns triggered worldwide changes in the daily routines of human experience. The Blursday database provides measures of subjective time and related processes from more than 2,800 participants (over 9 countries) tested on 14 questionnaires and 15 behavioral tasks during the Covid-19 pandemic. The easy-to-process database and all data collection tools are made fully accessible to researchers interested in studying the effects of social isolation on temporal information processing, time perspective, decision-making, sleep, metacognition, attention, memory, self-perception, and mindfulness. Blursday also includes vital quantitative statistics such as sleep patterns, personality traits, psychological well-being, and lockdown indices. Herein, we exemplify the use of the database with novel quantitative insights on the effects of lockdown (stringency, mobility) and subjective confinement on time perception (duration, passage of time, temporal distances). We show that new discoveries are possible as illustrated by an inter-individual central tendency effect in retrospective duration estimation.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".