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Record W3148046549 · doi:10.1257/app.20180168

Subways and Urban Air Pollution

2021· preprint· en· W3148046549 on OpenAlexaff
Nicolas Gendron-Carrier, Marco Gonzalez-Navarro, Stefano Polloni, Matthew A. Turner

Bibliographic record

VenueAmerican Economic Journal Applied Economics · 2021
Typepreprint
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsMcGill UniversityCenter for Interuniversity Research and Analysis on Organizations
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsParticulatesEnvironmental scienceAir pollutionPollutionEnvironmental engineeringGeography

Abstract

fetched live from OpenAlex

We investigate the effect of subway system openings on urban air pollution. On average, particulate concentrations are unchanged by subway openings. For cities with higher initial pollution levels, subway openings reduce particulates by 4 percent in the area surrounding a city center. The effect decays with distance to city center and persists over the longest time horizon that we can measure with our data, about four years. For highly polluted cities, we estimate that a new subway system provides an external mortality benefit of about $1 billion per year. For less polluted cities, the effect is indistinguishable from zero. Back of the envelope cost estimates suggest that reduced mortality due to lower air pollution offsets a substantial share of the construction costs of subways.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.017
GPT teacher head0.244
Teacher spread0.227 · 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 designObservational
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 routes1
Has abstractyes

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