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New Buildings and New Spaces

2017· book· en· W4247465735 on OpenAlexaboutno aff
Aurora Wallace

Bibliographic record

VenueUniversity of Illinois Press eBooks · 2017
Typebook
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureContext (archaeology)Corporate governanceCapital (architecture)Quarter (Canadian coin)Investment (military)Value (mathematics)Power (physics)EngineeringHistoryArchitectural engineeringBusinessPolitical scienceFinanceArchaeologyPoliticsLawComputer science

Abstract

fetched live from OpenAlex

This chapter views the New-York Tribune and the New York Times —the first in the industry to use skyscraper architecture as the medium for corporate image construction—in the context of the growing power of the press. In the last quarter of the nineteenth century, the city was reimagined with new patterns of circulation, spaces, conduits, and nodes of power. Alongside the growth of the banking and insurance industries, the press colonized lower Manhattan and the value of land rose precipitously. New construction and printing technology required capital investment and new forms of corporate governance. Media architecture transformed from rented space in low buildings to purpose-built signature buildings with lawyers, press agents, and advertising firms as tenants. The shift to taller buildings reveals a preoccupation with both the symbolic and economic value of the skyscraper, as media content became more attentive to the built environment.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.010
Scholarly communication0.0090.008
Open science0.0010.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0430.007

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 head0.042
GPT teacher head0.195
Teacher spread0.153 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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