Relative geographic concentration of creative, other traded, and local industries using establishment data and Harvard's U.S. Cluster Mapping Benchmark Definitions
Why this work is in the frame
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Bibliographic record
Abstract
This paper examines the relative tendency of industries and industry clusters to be geographically concentrated. Creative industries defined as having distinct artistic creation and production-distribution components are examined. This extends previous observations that creative industries exhibit a relatively high degree of geographic concentration to examine whether two-sided market dynamics contribute to this concentration. Variance in the distribution of business establishments among U.S. metro areas for 978 industries is calculated using County Business Patterns data from the U.S. Census Bureau. The data is mapped to different clusters using Harvard University's U.S. Cluster Mapping Benchmark Definitions. The average variance of each cluster is calculated to measure relative concentration.•Richard Caves' definition of creative industries is used to identify industries characterized by a two-sided structure.•Harvard University's U.S. Cluster Mapping Benchmark Definitions are used to map creative industries to specific industry codes and industry clusters.•These two methods are applied to U.S. County Business Patterns data to examine the relative geographic concentration of two-sided creative clusters.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it