Information Technology and the Distribution of Inventive Activity
Bibliographic record
Abstract
We examine the relationship between the diffusion of advanced internet technology and the geographic concentration of invention, as measured by patents. First, we show that patenting became more concentrated from the early 1990s to the early 2000s and, similarly, that counties that were leaders in patenting in the early 1990s produced relatively more patents by the early 2000s. Second, we compare the extent of invention in counties that were leaders in internet adoption to those that were not. We see little difference in the growth rate of patenting between leaders and laggards in internet adoption, on average. However, we find that the rate of patent growth was faster among counties who were not leaders in patenting in the early 1990s but were leaders in internet adoption by 2000, suggesting that the internet helped stem the trend towards more geographic concentration. We show that these results are largely driven by patents filed by distant collaborators rather than non-collaborative patents or patents by non-distant collaborators, suggesting low cost long-distance digital communication as a potential mechanism.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".