Bibliographic record
Abstract
Although several writers have noted significant complementary features in the respective projects of Russian philosopher and cultural theorist Mikhail Bakhtin (1895–1975) and the French social thinker Henri Lefebvre (1901–91), to date there has not been a systematic comparison of them. This article seeks to redress this oversight, by exploring some of the more intriguing of these conceptual dovetailings: first, their relationship to the intellectual and cultural legacy of Romanticism; and second, their respective assessments of irony (including Romantic irony), and, more specifically, of the ironic register as a potential vehicle for socio-cultural criticism. Although the positions Bakhtin and Lefebvre stake out vis-à-vis these issues reveal many similarities – such as extensive use of Socrates in the writings of each – there are also significant differences, not least because Lefebvre’s understanding of Romanticism is more fully developed than Bakhtin’s. Accordingly, the central argument advanced here is that Bakhtin’s fairly disparaging account of Romanticism, together with his scattered and often contradictory remarks on irony, can be subjected to re-envisioning and potential enrichment by reference to Lefebvre’s more considered thoughts, especially the latter’s notions of ‘Revolutionary romanticism’ and ‘Marxist irony’.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".