The Iron Cage of Enterprise or the Restoration of Class Power? Approaches to Understanding Neoliberalism
Bibliographic record
Abstract
Recent Foucauldian critiques of neoliberalism – especially those by Wendy Brown, Béatrice Hibou, and Pierre Dardot and Christian Laval – have argued that the Marxist interpretation of neoliberalism as a class project is reductive and economistic, and have instead conceptualised neoliberalism as a form of governmental rationality. This article compares these two influential approaches to understanding neoliberalism. It will outline the central features of the Foucauldian and Marxist approaches, assess the strengths and weaknesses of both approaches, and argue that a synthesis of the two approaches is both possible and desirable. While the Foucauldian approach enables a microphysics of everyday neoliberalism and its modes of subjectivity, it is argued that such an analysis must be placed within the broader, macrostructural approach of Marxism. The article thus defends Marxism against its Foucauldian critique, while nonetheless encouraging Marxists to engage with Foucauldian accounts of neoliberalism which they have so far tended to ignore.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.027 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".