Bibliographic record
Abstract
She develops the theory of cryptomimesis, a term devised accommodate the convergence of philosophy, psychoanalysis, and certain stylistic, formal, and thematic patterns and motifs in Derrida's work that give rise questions regarding writing, reading, and interpretation. Using Edgar Allan Poe's Madeline and Roderick Usher, Bram Stoker's Dracula, and Stephen King's Louis Creed, she illuminates Derrida's concerns with inheritance, revenance, and haunting and reflects on deconstruction as ghost writing. Castricano demonstrates that Derrida's Specters of Marx owes much the Gothic insistence on the power of haunting and explores how deconstruction can thought of as the ghost or deferred promise of Marxism. She traces the movement of the phantom throughout Derrida's other texts, arguing that such writing provides us with an uneasy model of subjectivity because it suggests that to be is haunted. Castricano claims that cryptomimesis is the model, method, and theory behind Derrida's insistence that learn live we must learn how talk Awith ghosts.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".