Bibliographic record
Abstract
This dissertation is a study of the complex effects of early modern corporate culture on English literature at the turn of the seventeenth century, when modern conceptions of the corporation were first taking shape. Then, as now, corporations were an intermediary source of identity and agency that could extend, complement, or contravene the work of the nation-state. But in early modern England the corporation was a more versatile form than it is now. This elasticity produces a curious moment of potential not only for overlapping identities but also alternative forms of political imaginary. The literary writers examined here lived in an era when corporations threatened, enabled, and extended the emergent focus on the rights of the individual subject. Accordingly, each chapter offers a case study in one of four canonical authors — Edmund Spenser, William Shakespeare, John Donne, and Ben Jonson — demonstrating through careful reading of their works how they conceived of and responded to the corporation as a political form for imagining their own and others’ relationships to the emerging English nation-state. The first two chapters focus on the figurative representation of the corporation as a discrete person. Chapter One recovers Spenser’s personification of an ancient Roman municipal corporation; this ancient form provides him with an ideal model for envisioning the English empire. Chapter Two then examines Shakespeare and his collaborators’ theatrical “personation” of a national corporation on stage, foregrounding the disjunctions between the imagined person and its embodiment in various representatives. The subsequent two chapters explore the ways early modern writers understood their personal and professional identities through the figurative lens of corporations. Chapter Three recovers Donne’s sense of “good company” as the nexus for his cosmopolitan connections to the political state and the world beyond. Chapter Four then demonstrates that Jonson’s anxious attempts to assert his independence from early modern corporate structures ultimately reinscribe these structures in his work. Overall, by recovering these complex early modern responses to corporate forms, these case studies defamiliarize our predominant sense of the corporation as a for-profit business enterprise and suggest historical alternatives in advance of the corporate relationships yet to come.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".