Growing microbiology literacy through interdisciplinary approaches to food fermentations and an Indigenous peoples’ rights framework
Bibliographic record
Abstract
New approaches to microbiology education are needed to ensure equitable representation in microbiology and to build literacy in microbiology and science broadly. To address this goal, we developed a course held at the collegiate level that uniquely integrated microbiology, Indigenous studies, science and technology studies, and arts and performance. The course participants included students in 12 majors across science, engineering, humanities, and arts. The different disciplines of the course intersected around Inuit fermented foods as the basis for discussions on fundamental microbiological principles, the scientific method, food sovereignty, and Indigenous peoples' rights. A diverse array of activities was included, ranging from lectures in microbiology and fermentation, a sauerkraut-making lab, a walk through the Native American contemplative garden, a workshop on Inuit drum making and dance, as well as a performance by Inuit-soul group Pamyua. We propose that a radically interdisciplinary approach and a human rights framework in microbiology education can be a way to enhance microbiology and science literacy for a diverse group of students.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".