Bibliographic record
Abstract
Throughout his short life in late 19th-century England, Joseph Merrick, known as the Elephant Man, was treated like a spectacle, sensationalized by doctors and scientists as much as by freak show owners. In his 1983 volume of poems Words for Elephant Man , Canadian poet Kenneth Sherman endows Merrick with a voice and “words” of his own, thus breathing life into this miserable creature. A close reading of Sherman&s;s poems is meant to illustrate that the poet is concerned with the Elephant Man not as a spectacle of sight but rather as a human being capable of “celebrating and singing his self” much in the vein of Walt Whitman. Sherman thus allows Merrick to transform from fascinating Other and object into a fundamentally unique self as subject that unfolds in his inviolable integrity from behind the mask of his facial disfigurement. The analysis is based on Emmanuel Levinas’ ethics of the face. Human beings encounter each other face-to-face, and the other&s;s face expresses the command to me that I respond ethically to them, thus granting them the opportunity to reveal themselves in the holiness of their wholeness. The disfigured face becomes a huge challenge against this backdrop.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".