Bibliographic record
Abstract
The bylaws of the American Literature Association stipulate the writ-ing every ten years of on the of the The present collection Literature in an Age of Globalization represents the latest in the series and is a follow up to Charles Bernheimer's Literature in the Age of Multiculturalism (1994). The structural similarities between the two titles, with their repetition of Comparative Literature in the âge of is striking, and I will corne back toit. The nineteen essays in the collection hâve been written by a team of eminent scholars and they respond not only to Bernheimer's collection and to the general theme of globalization but also to each other. The resuit is an interesting series of kaleidoscopic interventions, some highly readable and pulling lots of punch; others less user-friendly and, in attempting to arise to the occasion, somewhat convoluted and over-written. Granted: the report is a very awkward genre for which there are no rules and, given this need to improvise, the editer Haun Saussy has made a good job of providing a nuanced and multiperspectival account of the state of the discipline. It would hâve enhanced the impact of the present volume, however, had it been at times less an inward looking colloquy among seniors and more inviting to the as-yet not initiated graduate student. As it is, it makes very interesting reading for the diehard senior member of staff (and presumably the members of the ACL A) while being less accessible to the future scholar or to those working in other disciplines and interested in finding out what Literature stands for, where it is going to, and why it might be important.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.018 | 0.043 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".