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Record W2285918877 · doi:10.5148/tncr.2015.7203

Offshoring and Business Organization: Evidence from Canadian Manufacturing Firms

2015· article· en· W2285918877 on OpenAlexvenueaboutno aff
Lydia Couture, Jianmin Tang, Beiling Yan

Bibliographic record

VenueTransnational Corporation Review · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsOffshoringBusinessIndustrial organizationLinkage (software)Manufacturing sectorInternational businessCommerceMarketingOutsourcingEconomicsLabour economicsManagement

Abstract

fetched live from OpenAlex

In the globalized economy, it has become essential for firms to re-organize their production to grow and to be competitive in both domestic and international markets. Over the past decade, offshoring has emerged as an important and valuable business re-organization avenue, especially in the manufacturing sector. Using newly linked Canadian manufacturing micro data for 2002–2006, which for the first time provides a direct measure of offshoring over a period in Canada at the firm level, this paper examines and estimates the linkage between offshoring and business organization. It shows that offshoring is part of firms' overall business strategy, closely linked to other outward-oriented business activities such as exporting and being foreign-controlled. In addition, it is found that offshoring is associated with business organization in terms of firm variation in intermediate input variety and in output concentration.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.983
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.028
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.141
GPT teacher head0.233
Teacher spread0.092 · 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 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

Citations8
Published2015
Admission routes2
Has abstractno

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