Designing the Microbes and Social Equity Symposium: A Novel Interdisciplinary Virtual Research Conference Based on Achieving Group-Directed Outputs
Bibliographic record
Abstract
The Microbes and Social Equity working group was formed in 2020 to foster conversations on research, education, and policy related to how microorganisms connect to personal, societal, and environmental health, and to provide space and guidance for action. In 2021, we designed our first virtual symposium to convene researchers already working in these areas for more guided discussions. The symposium organizing team had never planned a research event of this scale or style, and this perspective piece details that process and our reflections. The goals were to (1) convene interdisciplinary audiences around topics involving microbiomes and health, (2) stimulate conversation around a selected list of paramount research topics, and (3) leverage the disciplinary and professional diversity of the group to create meaningful agendas and actionable items for attendees to continue to engage with after the meeting. Sixteen co-written documents were created during the symposium which contained ideas and resources, or identified barriers and solutions to creating equity in ways which would promote beneficial microbial interactions. The most remarked-upon aspect was the working time in the breakout rooms built into the schedule. MSE members agreed that in future symposia, providing interactive workshops, training, or collaborative working time would provide useful content, a novel conference activity, and allow attendees to accomplish other work-oriented goals simultaneously.
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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 | 0.025 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".