Bibliographic record
Abstract
Nominally addressed to the “museum,” this essay delineates its broad features in the Romantic period, a time of remarkable experimentation and growth, while exploring the adjacent possibilities of a digital “museum” such as RÊVE ( Romantic Europe: The Virtual Exhibition ) . Recovering the imaginative and eclectic model of the early modern curiosity cabinet, a form of gathering and containment for the notable and the contingent that actively engages the beholder in making connections, I approach the museum less as a fixed place or structure than as a scene of action (or related actions) that bears closely on Romanticism and its materialities, particularly in the realm of memory, mobility, interiority, temporality, and presence. The museum, in this way, is what it does , or what it enables us to do, as we organize, frame, and document (as well as overlook, misappropriate, and forget) the ever-rising tide of material things that marked the turn of the nineteenth century. From paintings to travelling cases, reliquaries to trees, folding screens to books, writers’ chairs to locks of hair, RÊVE ’s exhibits perform or repeat the museum’s essential gestures by assembling and mediating objects for our considered inspection, while making space for things to form associations, to re-member, to move—and in turn, to move us.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.257 | 0.077 |
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".