Topical Analysis of Nuclear Experts' Perceptions of Publics, Nuclear Energy, and Sustainable Futures
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
Nuclear energy experts consider commercial power from fission to be a strong contender to help mitigate the increasing effects of climate change, in part due to its low-to-no carbon emissions. Nevertheless, nuclear energy's history, including meltdowns such as Three Mile Island, Chernobyl, and Fukushima, and dumping in sacred Indigenous land such as Yucca Mountain, raises important concerns in public deliberation over nuclear power. These communicative dynamics are crucial to study because they inform larger conversations in communication scholarship about the role of experts in scientific controversies and the complicated nature of public trust in and engagement with science. Thus, this study explores the perspectives of experts and how they make sense of their own communicative practices through a topical analysis of semi-structured interviews with 12 nuclear scientists and engineers in the United States and Canada. Our analysis revealed four major topoi : (1) risk and safety, (2) government and policy, and (3) public education and engagement, and (4) cost, along which nuclear experts make sense of science-public boundaries and their role as scientists and scientist citizens. This paper extends our understanding and how scientists view themselves as communicative actors and the barriers and opportunities for how we can foster productive technical-public relationships around climate change solutions.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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