Escaping the Desert: On Roberto Unger, Pragmatism, and Critical Legal Studies’ Heterogeneity
Bibliographic record
Abstract
Recent scholarship on the legacy of Critical Legal Studies has emphasized the distinctiveness of the works of Roberto Unger. Some have argued that Unger has avoided the determinism created by functionalist accounts of history as well as the “intellectual desert” into which the deconstruction branch of CLS, and its focus on the indeterminacy of law, has led legal scholarship. However, beyond stating that Unger never espoused functionalist determinism nor the deconstruction branch’s radical indeterminacy, little has been said about the features of his writing that allowed him to reach this position. This essay offers an account of the specificity and success of Unger’s work. After laying out the differences between the works of Unger and the deconstruction branch of CLS, I argue that it is Unger’s espousing of a pragmatist methodology distinct from deconstruction’s Derridean inspiration that allowed him to escape the double-bind of functionalist determinism and radical indeterminacy.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.097 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| 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".