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Record W4378213519 · doi:10.17673/ip.2021.6.12.1

URBAN PLANNING AND HEALTH

2023· article· en· W4378213519 on OpenAlexaboutno aff
Vasily Filippov

Bibliographic record

VenueInnovative Project · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsHuman settlementUrban planningOpposition (politics)ArchitectureSanitationQuarter (Canadian coin)Mental healthGreat DepressionEconomic growthPolitical scienceHistorySociologyPoliticsCivil engineeringPsychologyMedicineLawArchaeologyEngineeringEconomics

Abstract

fetched live from OpenAlex

The evolution of ideas about the protection of the health of city residents is shown, starting with the emergence of the very science of urban planning in the last quarter of the 19th century. If in the works of its founder, Reinhard Baumeister, in relation to the health of citizens, the main attention was paid to their physical condition, namely sanitation and hygiene, then in the works of Camillo Sitte and Josef Stbben, who completed the formation of classical urban planning science, attention began to be paid not only to their physical, but and mental health and well-being. Ebenezer Howards idea of a garden city, which appeared as if in opposition to classical urban planning, actually turned out to be its development, as indicated by the successful implementation of the settlements of the Weimar Republic and Clarence Perrys neighborhood units, as examples of the integration of Howards ideas directly into the big city. Separately, the architecture of Swiss mountain resorts is considered, which is entirely subordinated to the promotion of health, and therefore had a direct impact on the entire architecture of the 20th century and its urban planning. In terms of time, this study is limited by the beginning of the global economic crisis of 1929 and the Great Depression, which resulted in radical changes in urban planning, due to which the issues of physical and mental health of city residents faded into the background.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.525
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.187
GPT teacher head0.448
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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