Bibliographic record
Abstract
Abstract: Twenty-five years ago, Robert K. Martin published an important essay that explored the gendered anxiety of authorship that left its traces throughout Nathaniel Hawthorne’s career. Given that novel-writing was understood in mid-nineteenth-century America as an essentially feminine occupation, did Hawthorne perceive himself as emasculated? Savoy supplements Martin’s argument by taking up the “fiction” of authorship, specifically the personage of “Nathaniel Hawthorne” that is constructed in “The Custom-House.” Previously, Savoy focused on Hawthorne’s gothic poetics as the figurative matrix within which the “author” accepts the exhortation of Surveyor Pue to fulfill his “filial duty” by delivering to the public the historical romance of Hester Prynne. This new article explores the “psychic economy” of what Jacques Derrida conceptualizes as the event of the archive—that is, the performative ways in which subjects are constituted precisely as subjects, in conformity with the regulatory ideals of nation, religious tradition, and gender. If there is no subject without a subtending and largely mythical archive of cultural practice, then “The Custom-House” is a spectacular mise-en-scène—rhetorically rich and charged with affect—of the ritualistic protocols of assujettissement.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".