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
Despite the occasional upsurge of climate change scepticism amongst Anglophone conservative politicians and journalists, there is still a near-consensus amongst climate scientists that current levels of atmospheric greenhouse gas are sufficient to alter global weather patterns to disastrous effect. The resultant climate crisis is simultaneously both a natural and a socio-cultural phenomenon and in this book Milner and Burgmann argue that science fiction occupies a critical location within this nature/culture nexus. Science Fiction and Climate Change takes as its subject matter what Daniel Bloom famously dubbed ‘cli-fi’. It does not, however, attempt to impose a prescriptively environmentalist aesthetic on this sub-genre. Rather, it seeks to explain how a genre defined in relation to science finds itself obliged to produce fictional responses to the problems actually thrown up by contemporary scientific research. Milner and Burgmann adopt a historically and geographically comparatist framework, analysing print and audio-visual texts drawn from a number of different contexts, especially Australia, Britain, Canada, China, Finland, France, Germany, Japan and the United States. Inspired by Williams's cultural materialism, Bourdieu's sociology of culture and Moretti's version of world systems theory, the book builds on Milner’s own Locating Science Fiction to produce a powerfully persuasive study in the sociology of literature.
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.011 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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