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Record W2598226466 · doi:10.5070/bp328133865

INNOVATION, THE AGRICULTURAL BELT, AND THE EARLY GARDEN CITY

2017· article· en· W2598226466 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBerkeley Planning Journal · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Landscape Design
Canadian institutionsMcGill UniversityUniversity of Calgary
Fundersnot available
KeywordsAntithesisSpace (punctuation)AgricultureLandscape architectArchitectureSociologyEconomic geographyEconomic historyArt historyArchaeologyHistoryGeographyLandscape architectureArtCivil engineeringEngineeringPhilosophy

Abstract

fetched live from OpenAlex

The emergence of the Garden City movement, inspired by Ebenezer Howard’s book To-morrow: a Peaceful Path to Real Reform (1898), subsequently published as Garden Cities of To-Morrow (1902), would have an enormous impact on future urban development and town- planning worldwide (e.g., Parsons and Schuyler 2002, 78; Ward 1992; Cooke 1978). Lewis Mumford claimed that the two most important inventions of the early twentieth century were the airplane and the Garden City (Mumford 1960). The Garden City model in many ways represents the antithesis to the historic city, as a model derived from smaller rural communities with a defined size, low densities, and a wealth of green space. Many subsequent urban models have expanded upon, altered, and diverged from Howard’s ideas. The Gar- den City has radically challenged the expectation that a city is a dense, vibrant, and largely hard-landscaped environment. In fact, urban environments developed over the last half-century have in many cases been dispersed, low-intensity, and soft-landscaped en- vironments, resulting in substantial changes to the way cities are constructed, managed, and inhabited.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.022
GPT teacher head0.240
Teacher spread0.218 · 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