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Record W6908359237 · doi:10.26153/tsw/58239

How Houston can prioritize pedestrians over vehicles with the strategic removal of freeways

2021· dissertation· en· W6908359237 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTexas Digital Library (University of Texas) · 2021
Typedissertation
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownSustainable transportRedevelopmentSustainabilityTransportation infrastructureSustainable development

Abstract

fetched live from OpenAlex

Houston is a city that heavily relies on its freeways for transportation and development. However, these freeway structures are approaching their expiration dates, and the City of Houston must decide on viable transportation methods moving forward. Will Houston choose sustainable transportation solutions that promote pedestrians over vehicles or choose traditional costly methods of maintaining and expanding freeway infrastructure? This report seeks to take the lessons learned from case studies and apply them to sustainable urban design solutions for Houston. This report is timely as Houston recently proposed a controversial North Houston Highway Improvement Project (NHHIP) which calls for the action of expanding portions of its freeways from downtown to the outer edge of the city. This report focuses on 11 case studies of cities who have removed or are considering the removal of their freeway structures. The five case studies I looked at in the United States were The Central Freeway in San Francisco, The Park East Freeway in Milwaukee, The Harbor Drive in Portland, The I-490 Inner Loop in Rochester, The Alaskan Way Viaduct in Seattle. The case studies in other countries were the Georges Pompidou Expressway in Paris and the Cheonggye Freeway Seoul. The case studies considering removing infrastructure were BQE Expressway in New York, The Claiborne Expressway in New Orleans, I-35 in Austin, and The Gardiner Expressway in Toronto. All case studies were meticulously reviewed, and the results of the cities that chose to remove infrastructure were documented. It was found that cities who chose to remove freeways experienced benefits that revitalized their communities and boosted their economies. Freeway removals did lead to gentrified neighborhoods although policies like affordable housing were found to help temper displacement effects. Data from case studies also revealed that freeway removal did not appear to seriously sacrifice transportation performance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.183
Teacher spread0.170 · 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