An architecture for people: a vertical neighbourhood for fostering social interactions
Bibliographic record
Abstract
Architecture should respond to the human need for social interaction, which can contribute to human health and well - being and support the sustainable growth and development of cities. Currently, world growth and development of cities. Currently, world–wide, high-density developments are recognized as a way to grow sustainably. Similarly, this has been recognized in the City of Toronto. However current condominium developments have primarily responded to the influx of young professionals and have overlooked the necessity for social interaction and consequently these facets have contributed to creating a monoculture in the downtown core. Nevertheless, to grow sustainably, the City of Toronto should focus on making densification a viable solution for a greater number of people, by accommodating for a variety of family types, and by responding to peoples’ need to interact socially. To achieve both of these goals requires: the management of large populations through the generation of clusters ,the integration of communal spaces, a circulation system to provide choice and generate encounters ,and a response to context.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".