Thickening the Public Realm: Choreographing the Interaction of the Public Realm with the Built Environment
Bibliographic record
Abstract
The ground plane has always been the primary domain of public activities. However, cities developed under the Modernist influence demonstrate an “object-in-space” circumstance with proliferating sky-scrapers that fragment the city’s ground surface into mid-block spaces and vaguely defined plazas. The demands of motorized-transportation and private enterprise further scatter spaces for pedestrian activities across the plan, section and stratified layers of the city (subterranean or/and elevated networks).The result is an inconsistent public realm that remains from being animated by public vitality. Through the manipulation of the ground-plane, this thesis seeks to remedy such stratification. It posits that a thickening of the ground to create a three-dimensional spatial condition will amplify opportunities for social interaction within otherwise muted civic surfaces. Addressing the contemporary reality of the multiplied ground, this thesis advocates reactivating it as a thickened continuous public domain that dissolves the polarity between the built and social fabric of the city.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.044 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".