Bibliographic record
Abstract
Judith Butler and Catherine Malabou’s recent exchange, ‘You Be My Body for Me: Body, Shape and Plasticity in Hegel’s Phenomenology of Spirit’, is remarkable because in their rereading of Hegel’s famous lord and bondsman parable, rather than focusing on recognition, work, or even desire, Butler and Malabou each wonder about how Hegel contributes to a new way of thinking about ‘having’ a body and how coming to ‘be’ a body necessarily involves a kind of dispossession. Butler and Malabou’s reading of Hegel is congruent with a current shift on the left away from a liberal politics of recognition to a (post-)Marxist analytic of dispossession: a move, in other words, away from liberal ‘solutions’ of redistribution – of either goods or recognition – towards thinking through issues of settler colonialism, forced migration and empire. Butler and Malabou’s piece points towards the insight that Hegel’s parable must be thought in terms of the political history of possessive individualism, and so in terms of the history of juridically defined property relations; the history of regarding both the body and the land as property. The ‘two valences’ of dispossession, in other words, refers in fact to a logic of property relations, one between those who ‘have’ property (either land or the property of their own bodies) and those who are juridically defined as propertyless.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.030 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".