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Record W1742933218

Slow Boiling the Economic Frog: A Historical Perspective on Offshoring

2007· article· en· W1742933218 on OpenAlexvenueno aff
Jan P. Muczyk

Bibliographic record

VenueJournal of Comparative International Management · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education and Engineering Focus
Canadian institutionsnot available
Fundersnot available
KeywordsOffshoringProfit (economics)EconomicsOutsourcingIndustrial organizationBusinessInternational tradeCommerceMicroeconomicsMarketing
DOInot available

Abstract

fetched live from OpenAlex

The “Theory of Comparative Advantage” has been used to justify international trade and offshoring. However, the theory is predicated on the immobility of factors of production, and that no longer is the case. The world-wide fiber optic network creates a superhighway to all the workforces of the world for all jobs or parts of jobs that can be digitized. While consumers, some investors, and some executives profit from offshoring, many jobs, especially manufacturing, are lost, and they will not be replaced by high tech jobs created by an innovative and flexible economy. Hence, recommendations have been advanced to create greater import/export parity, even if it means higher prices and more inflation.

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)0.003
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.008
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0060.025
Scholarly communication0.0080.014
Open science0.0010.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.048
GPT teacher head0.365
Teacher spread0.317 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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