On the quantity and quality of knowledge - the impact of openness and foreign research and development on North-North and North-South technology spillovers
Bibliographic record
Abstract
Knowledge accumulation means either new knowledge (an increase in its quality), greater access to existing knowledge (an increase in its quantity), or both. The authors examine the relative contribution of these two components of knowledge to total factor productivity (TFP) for North-North and North-South trade-related knowledge diffusion, with quantity, proxied by openness, and quality by the research and development (R&D) content of trade. The measure of foreign R&D used in the literature on trade-related knowledge diffusion, imposes equal contributions to TFP of openness, and of R&D content of trade. The authors'analysis show that R&D has a greater impact on TFP, than openness for North-North trade and, conversely, openness has a greater impact on TFP, than R&D for North-South trade. These results imply that the impact of openness on TFP in developing (industrial) countries is larger (smaller) than previously obtained in this literature, and that developing countries can obtain larger productivity gains from trade liberalization than previously thought.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
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".