Exploring Biological Variation and the Value of Natural History Collections Using an Online Lesson
Why this work is in the frame
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Bibliographic record
Abstract
First-year science students in large-enrollment lecture courses are rarely given opportunities to contribute to science beyond their classroom as part of their curriculum. Meanwhile, natural history museums are eager to engage students and the general public in curation and research projects, but cannot risk damage to irreplaceable specimens and typically do not have the resources to manage volunteers on the scale of a large university course. One such museum is the Beaty Biodiversity Museum (BBM) at the University of British Columbia (UBC), Canada. The BBM is home to UBC’s natural history collections and contains over two million specimens, but, like any natural history museum, specimens are not physically accessible to the general public, including university students. This lesson was designed to be online, with only a short project introduction and wrap-up happening in class, in order to both protect specimens and allow large numbers of students to participate in a museum curation project. A set of readings and videos introduce students to biological diversity and how it is documented in natural history museums, in this case, an herbarium. Along the way, students complete three worksheet activities exploring (i) physical variation within a single species, (ii) how specimens are preserved and digitized, and (iii) how new scientific questions can be asked using digitized biodiversity data. During this lesson, students digitize herbarium specimen labels and make a meaningful contribution to science beyond their own classroom. A pre- and post-survey capture student knowledge and perceptions of biodiversity before and after the lesson. <em>Primary Image:</em> Two herbarium specimens of the bull kelp, <em>Nereocystis luetkeana</em>, demonstrating physical variation within a species. Images from the Consortium of Pacific Northwest Herbaria, used with written permission from Richard Olmstead, CPNWH Administrator.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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