In the Lawscape - Introduction to the Edited Collection 'Law and the City'
Bibliographic record
Abstract
In this introduction to the edited collection 'Law and the City' by A. Philippopoulos-Mihalopoulos, a survey of the current literature of law and urban geography is sketched. Special emphasis is given to feminist legal geography, environmental law and space, body and the law and other critical legal theoretical strands that in one way or another attempt to capture the elusive connection between the law and the city. In order to advance such an understanding of the connection, the text builds on existing research and suggests 'the lawscape', namely the bringing together of law and the city, the logos and the polis, in a pairing that is determined by the law and the city's needs to be mutually conditioned (regulated, arranged, delimited) by the other. While the one constitutes the horizon for the other, at the same time each one is constitutive of the other in ways that belie any impression of epistemic or even ontological distance between the two. The text closes with a brief description of each one of the fifteen chapter-lawscapes that make up the edited collection 'Law and the City', which include Berlin, London, Panjim, Istanbul, Manhattan, Athens, Dar-es-Salaam, Moscow, Singapore, Johannesburg, Sydney, Toronto, Brasilia, Mexico city, and the Cybercity, as written by some of the most original and thought-provoking theorists of contemporary critical legal theory.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.073 | 0.018 |
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".