Of Labs and Other Places: (Literary) Criticism in the Age of Social Innovation
Bibliographic record
Abstract
In the aftermath of 2008, as economic planners grapple with the concurrent onset of secular stagnation and anthropogenic climate change, states have become increasingly jealous custodians of the public purse.In many of the world's advanced economies, policymaking has turned toward the use of "social innovation" funding frameworks that target scarce resources toward precisely-designated areas of strategic concern.The net effect of this process has been to prioritize the development of lab-based interdisciplinary research networks that are tasked with responding to a vexing cluster of "future challenge areas."Researchers from across the disciplines are now expected to demonstrate the social, economic, or environmental "impact" of their research.In this broader context, celebration of literature's "uselessness," long one of its special boasts, has become increasingly difficult to justify or sustain.It is admittedly hard to project what kind of contribution literary scholarship can make in this ends-oriented research context.All the same, this dissertation commits itself to running reconnaissance.Rather than blankly repudiate these new funding frameworks and R&D initiatives as neoliberal corruptions of a pastoral Keynesian campus -itself an expression of, and ideological bulwark to, the disastrous postwar modernization project -I ask how we might explore them as a new terrain of struggle, one whose characteristic constraints and dangers we can foreground together, self-reflexively.These are, after all, the kinds of questions that early-stage researchers will negotiate in practice, if not in theory, as they navigate R&D platforms and lab networks that more and more clearly subsist at the fraught intersection of a diverse array of conflicting "stakeholder" interests and commitments.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.083 |
| Scholarly communication | 0.025 | 0.018 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".