Introduction to Special Issue: The Function of Ecocriticism; or, Ecocriticism, What Is It Good For?
Bibliographic record
Abstract
How effectual is ecocriticism at practically addressing our most pressing and poignant global environmental issues? What hope through words? We organized this special issue of the Journal of Ecocriticism to consider the application and relevance of our-kind-of-thing, this marriage between words, texts, and earth; between criticism and trees; between the library carrel and the Greenland ice sheet. Tasked to consider how such a project operates within the strictures of ephemeral literary criticism while simultaneously considering what happens on the ground, “The Function of Ecocriticism” demands that its contributors juggle the competing burdens of rhetoric and activism, and reflect on whether the modus operandi of the former has any purchase on the ethical demands of the latter. We fear, however, that our efforts in this endeavor come to more of the same: words upon words, while elsewhere the fearsome and composed economic imperatives that brought us to this place at this time charge ever onward. This ecocritical experiment surely forces us to ask an obvious but no less difficult question: Are we also part of the problem? Each contributor to this volume—like all ecocritics—must tackle the inevitable: What is to be done? That they do so in such disparate ways points to the lively welter that is ecocriticism, as well as to the white noise of ecocide that hums in the not-so-distant background.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.057 | 0.022 |
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".