Bibliographic record
Abstract
Abstract The following experimental text is drawn from my most recent research project War Machines: Utopia and Allegorical Poetics in the Twenty-First Century. The project is an adaptation of the allegorical poetics developed by the French poet Charles Baudelaire in his scathing attacks on the sweeping transformation of Paris being conducted by Napoleon III’s right-hand man, Baron Haussmann. This small excerpt from my new book is a demonstration of my critical and poetical re-framing of Benjamin’s work that orients itself more towards the overlooked elements of Benjamin’s Marxism, as well as his “weak messianic” perspective, in order to re-assert a more radical orientation of his poetics and critical method with the utopian perspectives found in the work of that other great Marxist outlier of the twentieth century, Ernst Bloch, especially as outlined in his book, The Principle of Hope. Thus, unlike the postmodern appropriation of Baudelaire and Benjamin, I want to propose the possibility of bridging the gap between allegorical poetics, Marxism, and utopianism once again as a rigorous, critical option in the twenty-first century.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.030 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.038 | 0.005 |
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".