The Communication of Science as an Integral Component to the Undergraduate Experience
Bibliographic record
Abstract
Communication is fundamental at all levels of scientific endeavors, not least of which is when scientists must speak or write about their field to the general public. While this should be considered part of a scientist's responsibility in general (in order to justify and promote public funding of science, influence policymaking decisions and create informed citizens in matters of science), it is particularly important to the alumni of our undergraduate Biology programs. Despite the fact that the majority of our Biology undergraduate students at the University of Ottawa do not pursue Graduate studies after finishing their degrees, traditional undergraduate programs in Biology have not offered much training in the communication of science to non-scientist audiences. It is therefore essential that our B.Sc. alumni are imparted with skills in the popularization of science, such as the ability to explain complex concepts without relying on technical terminology, as well as to be able to generalize from very specific scientific notions. I will present how I have integrated a learning of science communication at all levels of the undergraduate experience at uOttawa, from a rethinking of the examination process and in-class presentations, to an Honour's thesis in the Public Communication of Science.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.014 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".