Writing in the “Second Person Plural”: Ben Lerner, Ambient Esthetics, and Problems of Scale
Bibliographic record
Abstract
In this paper, I examine the way that Ben Lerner confronts what I describe as the Anthropocene’s problematic of scale. While the use of “scale” has become commonplace in recent environmental criticism, what scale actually means in terms of literary critique has been less clear. This article looks at three different ways that scale has been taken up by recent environmental critique, as a spatial, temporal, and esthetic term. I then argue that Ben Lerner’s novels approach these three different valences of scale through the use of ambience, creating texts that are able to move across scales. It isn’t that Lerner’s work prioritizes any one scale, whether that is geologic or esthetic. Lerner’s ambient writing, in effect, is able to understand how the large and the small work together co-constitutionally to create a literature for the Anthropocene.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".