Buenos Aires in 8,66: the regularity of the city as an opportunity to develop replicable prototypes
Bibliographic record
Abstract
Since its second foundation at the end of the 16th century, the urban fabric of the city of Buenos Aires has been organized as an orthogonal regular grid, struc- tured by 100m x 100m blocks. With the growth of the city in the 20th century, as well as its increasing density, every block in the city was divided into a regular number of plots each 8.66m wide, with a unique lot shape: Narrow and deep. Over time, the city has been molded by its demography and urban regulations. However, in December 2001 the most dramatic and deep-seated crisis in Argen- tina’s history erupted and gave place to what became known as “El Corralito”. This crisis has had a huge impact on the social fabric of the city and has led to a housing deficit that lasts until these days. This thesis develops a strategy that would allow the city to densify and solve its housing crisis. A strategy that proposes to use the fixed width of the plots of Buenos Aires to deploy in its layout an Absolute Architecture. To this end, each of the articles that make up this thesis will delve into the idio- syncrasy, physiognomy, and architecture of Buenos Aires in an attempt to reveal its essence, an essence that will be the material from which to imagine the con- temporary city.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".