Illegible Subjects: Knowledge and American Modernity, 1898-1985
Bibliographic record
Abstract
This dissertation explores the relationship between politics and knowledge as represented by a set of late-nineteenth and mid-twentieth century American writers. The category of knowledge has long been regarded as a site of power and has, consequently, also been a site of contestation. There is a suggestion that if the way the world is understood ramifies through the domains of the political and the social, then efforts must be made to—as Eve Sedgwick puts it—“pluralize and specify” knowledge in order to disentangle it from oppressive agendas. This mode of critical address has a lot of traction in the humanities and is differently exemplified by scholars such as Michel Foucault, Judith Butler, and Sylvia Wynter. I intervene in their conceptions about the relationship between knowledge production and social change by examining a series of American writers who, rather than remaking the normative codes that impose legibility on social and political life, work towards accessing the broad range of political possibilities that exist outside of what is either known or knowable. I begin by surveying the critical field that examines the relationship between knowledge, politics, and everyday life. In particular, the introduction draws upon the pragmatist philosopher William James and his critique of “vicious intellectualism” to develop what I call American society’s legibility imperative and consider how it can be undone. My first chapter demonstrates how the late writing of Henry James militates against modernity’s reduction of all aspects of life to what is profitable and quantifiable by celebrating forms of human subjectivity and relation that are purposeless, unpredictable, and porous. Next, I interrogate how Nella Larsen’s Quicksand suggests that the production of sustaining forms of collective life depends upon the suspension of the coercive demand that subjects exchange their radical opacity for identitarian legibility. My third chapter explores how the essays of James Baldwin contend that the imagining and creation of a better world is predicated upon rethinking the normative value accorded to knowledge in the practice of politics. I conclude with Djuna Barnes’s Nightwood which argues that doing away with knowledge’s priority could potentially lead to the emergence of an authentic, non-hierarchical, and trans-species community.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".