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Record W2122346327 · doi:10.1111/twec.12360

Impact of Trade on Canada's Employment, Skill and Wage Structure

2015· article· en· W2122346327 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

VenueWorld Economy · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsGovernment of Canada
Fundersnot available
KeywordsAutarkyEconomicsWageLabour economicsWelfareExchange rateHuman capitalHourly wageTechnological changeManufacturingFree tradeInternational economicsMonetary economicsBusinessMacroeconomicsEconomic growthMarket economy

Abstract

fetched live from OpenAlex

Abstract Using newly constructed data for 88 C anadian industries (including primary, manufacturing and services), for 15 years (1992–2007), we analyse the impact of trade and technological change on labour demand, skill structure, wage premiums and welfare in C anada. Results show that export growth has no impact, whereas import growth reduces employment growth. But contrary to popular belief, C anada's job loss due to imports has been very small, only about 6,000 persons annually. C hina's negative impacts are more pronounced in industries where the share of information and communication technology ( ICT ) capital is rising fast and among low R & D intensive industries. In terms of skill change, ICT use and real exchange rate appreciation are biased towards high skill workers. Imports from the United States and C hina are skill‐neutral, whereas imports from M exico are skill‐upgrading. Overall, neither export nor import growth has an impact on the wage rate. However, had there been no imports from China, the annual wage growth rate of high skill manufacturing workers would have been 0.6 per cent higher. Between 1992 and 2007, there was an annual net gain from the rise in imports at about 0.4 per cent of GDP , in addition to the gains obtained from 1992 import levels vis‐à‐vis autarky.

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 score0.304
Threshold uncertainty score0.900

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 head0.040
GPT teacher head0.219
Teacher spread0.179 · 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