Bibliographic record
Abstract
Abstract Utilizing industry‐level foreign direct investment (FDI) from 72 source markets to 122 destination markets between 2003 to 2018, we evaluate how cross‐border technology investments respond to economic recessions. We find that FDI embedded with intensive research and development (R&D) drops when the destination market is in a recession and the source market is in a normal state and recovers to the pre‐recession levels when both destination and source markets are in recession. However, there is little evidence that recessions affect cross‐border investments in other aspects of technology measured by the penetration of robots, intellectual property products and information and communications technology (ICT). The response of R&D‐intensive FDI to recessions is particularly pronounced in deep and long recessions, during the propagation stage of recessions and in destination markets with relatively weak institutional protection of intellectual property and rule of law, loose FDI regulation and high financial development. Our findings are limited to advanced markets: there is no evidence that R&D‐intensive FDI from or to emerging markets responds to either destination or source market recessions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".