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Record W4416331350 · doi:10.1080/00295450.2025.2527499

Atomic Eve: Exploring Science Fiction and Social Media to Increase Interest in Nuclear Energy Among Women

2025· article· en· W4416331350 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNuclear Technology · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSocial mediaEnergy (signal processing)Nuclear scienceNuclear powerAtomic energy

Abstract

fetched live from OpenAlex

Is it possible to increase interest in learning more about nuclear science among young women through science fiction? How can the interactive elements of social media advance #STEMINISM? Inspiring greater interest in radiation as an educational topic is important to recruiting the future generation of scientists and is crucial to the ability of Canada and other countries to deploy new nuclear power as part of the low carbon energy mix. This article explores how science fiction and social media could help address gender divides in scientific understanding of radiation and encourage more women and young people to pursue nuclear energy careers. While nuclear power can provide stable and clean electricity to replace fossil fuels, learning about nuclear science may be dismissed by today’s youth as “too boring” to reliably grow the workforce to meet future demands. Gender divides in scientific understanding of radiation include the tendency for more males than females to be employed in the nuclear sector, which reaches back to a more general trend in which females are underrepresented among STEM (science, technology, engineering, and mathematics) graduates. Even fictional depictions of radiation tend to be geared toward audiences or interests that are (at least historically) more identified as “for boys” than “for girls.” Science fiction storytelling provides a promising method of engagement to increase interest in nuclear science and possibly inspire more passion in STEM-oriented career paths among youth; however, strategies for overcoming the gender-biased limitations of the science fiction genre must be developed. This paper explores how science fiction and the social media platform Instagram can be combined to spark interest in nuclear energy as a climate change solution among women and young people. Atomic Eve is a science fiction Instagram superhero whose mission on Earth includes helping to solve the climate change crisis by increasing interest in learning more about nuclear energy. This article presents Atomic Eve as a creative experiment in how STEAM education (science, technology, engineering, arts, and mathematics) could help innovate thinking around the role of public engagement in inspiring more women and younger people to pursue careers in the nuclear energy sector.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.195
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it