Bibliographic record
Abstract
Stephen Knadler challenges the alignment of physical mobility with freedom by elaborating on the debt crisis and exclusion of the mobile freeman discursively constructed as a semi-citizen under mid-century racial capitalism. In doing so, he explores the limits to aligning African American autobiographical writing primarily with the slave narrative by making a case for the emergence of a new autobiographical genre that he calls the semi-citzenship narrative. Emerging in the decade before the Civil War and written predominantly, though not exclusively, by men, this genre complicates “understanding of the relation among antebellum citizenship making, Black freedom struggles and racial capitalism.” The semi-citizenship narrative, he argues, constitutes an ignored history of the “afterlife of free labor” that unsettles the racialization of Blackness as social and legal death and whiteness as free waged labor and citizenship. That unsettling is staged through a “quasi-citizenship” articulated in accounts of the freeman’s indebtedness and “excluding out” by writers such as William Grimes, Samuel Ringgold Ward, Thomas Smallwood, and Austin Steward. Knadler argues that these writers were using their narratives to account for the “unfolding and incomplete transition of the enslaved into a third term, a so-called free person who was not quite a citizen nor yet enslaved.”
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.003 |
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".