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Record W1488769922 · doi:10.3386/w20036

Information Technology and the Distribution of Inventive Activity

2014· preprint· en· W1488769922 on OpenAlexaff
Chris Forman, Avi Goldfarb, Shane Greenstein

Bibliographic record

VenueNational Bureau of Economic Research · 2014
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDistribution (mathematics)Computer scienceMathematics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.169
GPT teacher head0.404
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations14
Published2014
Admission routes1
Has abstractyes

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