Bibliographic record
Abstract
Foucault’s inspiration from Nietzsche in terms of his approach to the writing of history is difficult to overestimate. However, this article will advance an interpretation of Foucault’s approach to history which focuses on another, and less readily evident, dialogue partner in his authorship, namely the Marxist tradition and, more precisely, French Maoism. In the first part it is argued that Foucault’s practical experience from his involvement in the Maoist inspired activist group, Groupe d’information sur les prisons (GIP), left crucial marks on his contemporaneous statements on the genealogical method and his elaboration of the power-knowledge nexus. In the second part of the article it is demonstrated how the activism of GIP is reflected in his lectures at Collège de France in 1976. The aim of the article is threefold. Firstly, to bring attention to other (largely neglected) sources of inspiration for Foucault’s genealogical approach than Nietzsche. Secondly, to contribute to a more nuanced understanding of Foucault’s relationship to Marxism, which is frequently portrayed rather one-sidedly as unambiguously negative. And thirdly, to demonstrate concretely how principles originating from Maoist political activism reappear, not only in Foucault’s practical commitment to GIP, but also in his theoretical considerationsof genealogy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".