MétaCan
Menu
← Back to cohort
Record W4247920026 · doi:10.24124/2011/bpgub1489

BRIC and Canada's dependence: impact of manufacturing costs

2011· dissertation· en· W4247920026 on OpenAlexaffabout
Kristoffor E. Benson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsBRICChinaBusinessManufacturing sectorEmerging marketsIndustrial organizationInternational tradeEconomicsInternational economicsFinancePolitical science

Abstract

fetched live from OpenAlex

Brazil, Russia, India, and China together form the BRIC group of developing economies and are experiencing growth much greater than both the G7 and world as a whole. All four countries have significant ties to Canadian business and through the process of this project we will look at how our economic landscape is affected by their growth. The focus of this project will be on the manufacturing sector and how the rising cost of labour in the BRIC will affect Canadian producers and manufacturers. The research performed notes the increased cost of labour has reduced the benefits for Canadian companies to offshore their manufacturing requirements and goes on to demonstrate that this cost will exceed that of onshore manufacturing by 2025. Recommendations are made for the producers, manufacturers, and Canadian governments to both mitigate this risk and take advantage of the BRIC's growing economies. Primarily, these recommendations are focused on the onshoring of manufacturing. --P. ii.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.427

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0040.001
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.001

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 head0.030
GPT teacher head0.214
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2011
Admission routes2
Has abstractyes

Explore more

Same topicGlobal trade and economics→French-language works237,207→