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Record W4244879440 · doi:10.32920/ryerson.14652339

An architecture for people: a vertical neighbourhood for fostering social interactions

2021· preprint· en· W4244879440 on OpenAlexaffabout
Joanne Gust

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCollaborative and Sustainable Housing Initiatives
Canadian institutionsToronto Metropolitan University
FundersRobin Hood Foundation
KeywordsSustainabilityNeighbourhood (mathematics)Variety (cybernetics)DowntownContext (archaeology)ArchitectureEconomic geographyBusinessPolitical scienceEconomic growthSociologyEnvironmental planningGeographyEcologyComputer scienceEconomics

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.064
GPT teacher head0.404
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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