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
ABSTRACT This article contributes to a better understanding of dystopia’s practical aims by offering a critical defense of what Gregory Claeys calls the “Atwood Principle.” Derived from the writings of Canadian author Margaret Atwood, it establishes a yardstick for separating speculative fiction from science fiction. I argue that, rather than elevating it to the status of a genre definer, the Atwood Principle should be vindicated in terms of a heuristic device for contextually identifying the central mechanism underpinning dystopias: warning through extrapolation. The real challenge, then, is how to make sense of the complex functioning of extrapolation. Instead of viewing it in mechanistic terms, my suggestion is to envisage extrapolation as a dynamic process involving both realism and estrangement. I illustrate this through a contrast between two kinds of stories about the current climate emergency: cautionary and post-cautionary tales of the Anthropocene.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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