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Record W4404567195 · doi:10.1111/cwe.12556

Long‐term Effect of Export Expansion on Human Capital

2024· article· en· W4404567195 on OpenAlex
Jintao Fu

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.

Bibliographic record

VenueChina & World Economy · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTerm (time)EconomicsMonetary economicsInternational economicsHuman capitalBusinessMarket economy

Abstract

fetched live from OpenAlex

Abstract This paper illustrates how trade liberalization during an individual's early life can affect long‐term health and cognitive outcomes 15 years later (i.e., in adolescence). China's accession to the World Trade Organization has brought significant economic benefits but has also given rise to some environmental concerns. Exploiting variations in each prefecture's exposure to trade shock and trade‐induced pollution shock, this study constructed a shift‐share instrument variable model. The trade shocks in early life improved health and cognitive outcomes significantly during adolescence while trade‐induced pollution shock had the opposite effect, decreasing these two outcomes. These impacts were more pronounced among households with low economic status. Further investigation provided evidence for several underlying mechanisms, such as improved health and education resources and reduced SO 2 emissions by firms. This study provides useful insights into how to evaluate the long‐term effects of trade liberalization on human capital in terms of economic benefits and environmental costs in China.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.019
GPT teacher head0.235
Teacher spread0.216 · 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