Critical STEM Literacy and 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
The COVID-19 pandemic has resulted in unprecedented amounts of information communicated to the public relating to STEM. The pandemic can be seen as a 'wicked problem' defined by high complexity, uncertainty and contested social values requiring a transdisciplinary approach formulating social policy. This article argues that a 'Critical STEM Literacy' is required to engage sufficiently with STEM knowledge and how science operates and informs personal health decisions. STEM literacy is necessary to critique government social policy decisions that set rules for behaviour to limit the spread of COVID-19. Ideas of scientific, mathematical and critical literacy are discussed before reviewing some current knowledge of the SARS-CoV-2 virus to aid interpretation of the examples provided. The article draws on experience of the pandemic in the United Kingdom (UK), particularly mathematical modelling used to calculate the reproductive rate (R) of COVID-19, communication of mortality and case data using graphs and the mitigation strategies of social distancing and mask wearing. In all these examples, there is an interaction of STEM with a political milieu that often misrepresents science as activity to generate one dependable truth, rather than through careful empirical validation of new knowledge. Critical STEM literacy thus requires appreciation of the social practices of science such as peer review and assessment of bias. Implications of the pandemic for STEM education in schools requiring critical thinking and in understanding disease epidemiology in a global context are discussed.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| 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