Technology Spillover Effects by Undertaking International Service Outsourcing: Empirical Analysis Based on Software Industry in Service Outsourcing Base Cities of China
Bibliographic record
Abstract
The technology spillover effect is defined as resources like human capital,RD input,and managerial experiences in multinational corporations(MNCs)have been unconsciously spread out to recipient countries through MNCs' investment,which will promote technical progress and economic growth.This paper focuses on the technology spillover effects by undertaking international software outsourcing projects in China,using cross-sectional data of fourteen service outsourcing base cities.The results demenstrate that: By undertaking international software outsourcing projects,local software industry can improve it's productivity through technology spillover effects.And technology spillovers are largely through the demonstration effects of multinationals and cumulation effects of human capitals.The Chinese government should keep up the opening-up policy for software industry,improve the cumulation of human capitals in software industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".