Not Invented Here? Innovation in Company Towns
Bibliographic record
Abstract
We examine variation in the concentration of inventive activity across 72 of North America’s most highly innovative locations. In 12 of these areas, innovation is particularly concentrated in a single, large firm; we refer to such locations as “company towns.” We find that inventors employed by large firms in these locations tend to draw disproportionately from their firm’s own prior inventions (as measured by citations to their own prior patents) relative to what would be expected given the underlying distribution of innovative activity across all inventing firms in a particular technology field. Furthermore, we find such inventors are more likely to build upon the same prior inventions year after year. However, smaller firms in company towns do not exhibit this myopic behavior; they draw upon prior inventions as broadly as their small-firm counterparts in more diverse locations. In addition, we find no evidence that inventions from company town firms, large or small, have any less impact. However, inventions by large firms in company towns do seem to have a narrower impact in terms of geographic scope. Furthermore these firms appropriate a disproportionately large fraction of their impact themselves.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".