Bibliographic record
Abstract
Using plastic as a “theory machine,” this article looks into the dynamics and poetics of what I call plastic literature. It argues out a case for the “plastic sea” with its properties like sinking, mineralization, scopious contamination, pervasiveness, and deep-water micro-plasticization. The translocationality of plastic represents a spatial consciousness where plastic seeps into salt, water, soil, animal and human bodies, media, and our psychosis in non-linear, non-hierarchical, fragmentary mobility and fluidity; this does not discriminate between its point of origin and eventual destination, race, ethnicities, discriminations of colour, religious affiliations, cultural heritage, and political schoolings. Thus, plastic provokes connections/comparatism with a difference that speaks of becomings, dispersions, and immanence. Is plastic behaviour and agency not close to how we think of literature in a globalized world? Working out the other areas of the material aesthetic of plastic, the article connects plastic behaviour with literary habits and thinking. It homes in on “plastic lit(t)erization” to bring about a new poetics of thinking and doing literature. The article strings corresponding coordinates as made available through our understanding of plastic sea, networks of transmission, travel and transition, gradient flow, trans-corporeality, local-global fusion, process time, sink, and the discourses around hyper sea. Plastic literature becomes our new poetics of generating literary capital and rethinking world 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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.057 | 0.015 |
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".