MétaCan
Menu
Back to cohort
Record W2900146611 · doi:10.3368/le.95.2.157

Pollution and Politician Productivity: The Effect of PM on MPs

2019· article· en· W2900146611 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLand Economics · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsWestern UniversityUniversity of Ottawa
Fundersnot available
KeywordsEndogeneityHouse of CommonsParliamentPollutionProductivityLead pollutionQuality (philosophy)ConfoundingParticulatesEconomicsDemographic economicsEconometricsStatisticsPolitical scienceMathematicsLawEconomic growthChemistryPoliticsBiology

Abstract

fetched live from OpenAlex

Applying methods of textual analysis to all 119,225 speeches made in the Canadian House of Commons between 2006 and 2011, we establish that air pollution reduces the speech quality of Canadian members of parliament (MPs). Exposure to fine particulate matter concentrations exceeding 15 µg/m3 causes a 2.3% reduction in the quality of MPs’ speech (equivalent to a 2.6 month decrease in education). For more difficult communication tasks the decrement in quality is equivalent to the loss of 6.5 months of schooling. Our design accounts for the potential endogeneity of exposure and controls for many potential confounders including individual fixed effects. <i>(JEL Q52, Q53)</i>

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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