MétaCan
Menu
Back to cohort
Record W4413724912 · doi:10.1017/aee.2025.10052

What Were We Thinking? A Climate Fiction Beginning and Ending, Told Inside and Outside and Backward and Forward

2025· article· en· W4413724912 on OpenAlexaffabout
Alison Neilson, Sevgi Aka, Dwight Owens, Julia Jung, Małgorzata Suś

Bibliographic record

VenueAustralian Journal of Environmental Education · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaOcean Networks Canada Society
FundersCentro de Investigação em Ciências SociaisFundação para a Ciência e a TecnologiaUniversidade de Lisboa
KeywordsProject commissioningHistoryPublishingLiteratureSociologyAestheticsArt

Abstract

fetched live from OpenAlex

Abstract We resonated with the idea that dreaming is important, and that climate fiction is a way of dreaming with environmental educators. A well of resistance lives in art collaborations around the world which harness the power of the collective to face terrible realities and twist, bend, and dance them into alternative hopeful pasts, presents and futures. Engaging with other people and more-than-human lives, through creative collaborations have led us to understand complex and unfamiliar perspectives in ways that are unreachable alone, regardless of how much academic study we do. This story emerged from online meetings that crossed time zones and oceans: Vancouver to Istanbul. Our climate fiction surfaced from improvised, spontaneous story creation. It was as if the story was waiting for us to find her, if we acted with care and love while facing directly our own dark shadows and fears about climate catastrophe. This story of Cassandra, alongside our interpretations of its emergence, invites the reader to draw from any evoked confusion or other feelings as well as their own learnings to reflect on burdens of knowledge not acted upon. Leaning into confusion is a way to open up to the power of uncertainty for environmental education.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueAustralian Journal of Environmental EducationSame topicClimate Change and GeoengineeringFrench-language works237,207