COVID-19 and the courtroom: how social and cognitive psychological processes might affect trials during a pandemic
Bibliographic record
Abstract
Around the world, almost every aspect of people's lives has been affected by the novel coronavirus (COVID-19). We focused on one context that has received relatively little attention to date: the courtroom. Guided by established psychological findings and theories, we explored how the emergence of COVID-19 and proposed protective measures against the virus (i.e. face masks, physical distancing) could affect legal decision-making at trial. For the majority of the phenomena that we considered, the extant literature predicted negative or mixed effects. Because it appears likely that extralegal factors related to the pandemic will affect outcomes, the fairness of proceedings must be called into question. Overall, this work suggests that the reopening of the courts might be premature. It also highlights the importance of leveraging established psychological findings to address questions arising from unpredictable events when direct research is not yet available.
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How this classification was reachedexpand
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".