Emerging Standards and the Hybrid Model for Organizing Scientific Events During and After the COVID-19 Pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the beginning of 2020, the coronavirus disease (COVID-19) pandemic has dramatically influenced almost every aspect of human life. Activities requiring human gatherings have either been postponed, canceled, or held completely virtually. To supplement lack of in-person contact, people have increasingly turned to virtual settings online, advantages of which include increased inclusivity and accessibility and a reduced carbon footprint. However, emerging online technologies cannot fully replace in-person scientific events. In-person meetings are not susceptible to poor Internet connectivity problems, and they provide novel opportunities for socialization, creating new collaborations and sharing ideas. To continue such activities, a hybrid model for scientific events could be a solution offering both in-person and virtual components. While participants can freely choose the mode of their participation, virtual meetings would most benefit those who cannot attend in-person due to the limitations. In-person portions of meetings should be organized with full consideration of prevention and safety strategies, including risk assessment and mitigation, venue and environmental sanitation, participant protection and disease prevention, and promoting the hybrid model. This new way of interaction between scholars can be considered as a part of a resilience system, which was neglected previously and should become a part of routine practice in the scientific community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it