MétaCan
Menu
Back to cohort
Record W2098932544

The Earnings Effects of Multilateral Trade Liberalization

2012· article· en· W2098932544 on OpenAlex
Thomas W. Hertel, Maros Ivanic, Paul V. Preckel, John Cranfield

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

VenueThe World Bank Economic Review · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEconomicsEarningsPovertyConsumption (sociology)Per capitaFree tradeLiberalizationLabour economicsPer capita incomeInternational economicsPopulationEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

Most researchers examining poverty and multilateral trade liberalization have had to examine average, or per capita effects, suggesting that if per capita real income rises, poverty will fall. This inference can be misleading. Combining results from a new international cross-section consumption analysis with earnings data from household surveys, this article analyzes the implications of multilateral trade liberalization for poverty in Indonesia. It finds that the aggregate reduction in Indonesia's national poverty headcount following global trade liberalization masks a more complex set of impacts across groups. In the short run the poverty headcount rises slightly for self-employed agricultural households, as agricultural profits fail to keep up with increases in consumer prices. In the long run the poverty headcount falls for all earnings strata, as increased demand for unskilled workers lifts incomes for the formerly self-employed, some of whom move into the wage labor market. A decomposition of the pov...

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.032
GPT teacher head0.233
Teacher spread0.201 · 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