Chakravarty, Urvashi. Fictions of Consent: Slavery, Servitude, and Free Service in Early Modern England
Bibliographic record
Abstract
The three keywords that frame the argument in this book designate the three kinds of bound labour described in non-literary and literary texts in early modern England and in early British America.Urvashi Chakravarty's densely argued and compellingly written book shows slavery, servitude, and free service to be conceptually connected.But these terms also denote different structures and levels of agency of men and women subjugated to the master's power of rule and ownership of them.The argument shows in revealing detail and with ample original evidence that the early modern slave is not the same as the antique Roman kind, not the servus who worked on a latifundium, but the premodern type, the ancilla, or the household or domestic servant.As Chakravarty elucidates persuasively, the linguistic origin of the two concepts is shared but the valences of bound labour determine the nuances of this connection.These three keywords designate three closely related and intertwined phenomena rather than point to three different stages, from a total absence of freedom to manumission, through which a subject may go through in the temporal and spatial mapping covered by this consistently illuminating book.This deeply researched study is full of archival treasures.With critical acuity, Chakravarty shows that slavery and servitude both intersect and diverge as socio-cultural and literary phenomena.Where there is a critical line that separates the socio-cultural history of slavery from its equivalent in service, and where such a social picture diverges or coincides with literary fictions, represents a complex, provocative, and fascinating topic, one that is difficult to balance all the time.Yet Chakravarty's analysis finds persuasive solutions to this hermeneutic entanglement.A further complication is added by the introduction of consent (or unconsent at times), a term that is both conceptually and historically part of the cultural and fictional narrative of slavery and service.Again, Chakravarty's probing exploration of this critical intertwining of terms results in original analyses brimming with eloquent power that may well define the course and terms of further research.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| 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".