Simplification is Complicated: Property, Nature, and the Rivers of Law
Bibliographic record
Abstract
A number of scholars have criticized the ways in which property law simplifies nature. Such reductive simplifications are seen as being reliant upon a claim to mastery and dominion that is belied by the essential complexity and dynamism of the natural world. Drawing from a close reading of a property-boundary dispute involving the historical movements of the Missouri River, I supplement this account by revealing the ways in which legal simplication is itself complicated: that is, both dependent on considerable amounts of practical work, and subject to breakdown, ambiguity, and contradiction. Rather than a singular river, made legible through the unfolding of a unitary legal logic, I reveal several conflicting ‘rivers’ produced through property law. I conclude by trying to make sense of property as a set of practices that serve to produce the ‘effect’ of property. These practices, while often messy and contradictory, are, nevertheless, significant in the installation of property as a powerful organizing device through which the social world is made meaningful.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.045 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".