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Record W1604784576

Air pollution, foetal mortality, and long-term health: Evidence from the Great London Smog

2014· article· en· W1604784576 on OpenAlexaboutno aff
Alastair Ball

Bibliographic record

VenueMunich Personal RePEc Archive (Ludwig Maximilian University of Munich) · 2014
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Environmental healthAir pollutionDemographyPollutionTerm (time)MedicineParticulatesGeographyBiology
DOInot available

Abstract

fetched live from OpenAlex

This paper provides new evidence on the consequences of foetal exposure to high levels of pollution for the risk of stillbirth, and for the long-term health and labour market outcomes of those that survive. Variation in in utero exposure comes from a persistent weather system that affected London for five days in December 1952, preventing the dispersion of atmospheric pollution. This increased levels of total suspended particulate matter by around 300%. Unaffected counties in England and Wales are used in a differences-in-differences design to identify the short and long-term effects.
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\nHistorical registrar data for the nine months following the smog show a 2% increase in reported stillbirths in London relative to national trends. As foetal deaths often go unreported, the exercise is then repeated for registered births. The data show around 1600 fewer live births then expected in London, or a reduction of 3% against national trends. Survivors are then identified by district and quarter of birth, and their health and labour market outcomes observed at fifty and sixty years old. Differences-in-differences estimates show that survivors are in general less healthy, less likely to have a formal qualification, and less likely to be employed than those unaffected by the smog.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.081
GPT teacher head0.361
Teacher spread0.279 · 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 teacher head, not a consensus.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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