Bibliographic record
Abstract
The dead metaphor of “trash fiction” is in need of resuscitation or, better yet, of reincarnation. To recognize most any printed material as a disposable commodity suggests that those who are interested in discovering ways in which literature and environment interact would do well to begin by addressing the discipline’s own contribution to the world’s mass of disposable prose. Though ecocritical scholarship has drawn attention to important new themes for literary analysis, such studies are often conducted in much the same way as the cultural and formalist approaches they aim to supersede—asking the same kinds of questions, using the same methods to answer them, and conducting these debates in the same kinds of venues. In focusing so intently on the text’s ability to cast light upon elements of the environmental unconscious, the book’s role as an unconscious element of our modern environment has often been elided.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.023 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".