Bridging the Gap: Integrated Occupational and Industrial Approach to Understand the Regional Economic Advantage
Bibliographic record
Abstract
In the debates on regional economic analysis, scholars generally reach the consensus that the industrial frame and the occupational mix are not very accurate substitutes for each other. While industry concentration and mix are widely accepted as significant, the independent consideration of occupation has been shown to be important, especially for creativity-concentrated regions. However, neither the industrial nor the occupational mix is separately sufficient to be solely applied to understand the entire regional situation. This paper develops an integrated occupational and industrial structure (IOIS) at the state and also the national level in order to bridge the gap between separate industrial and occupational analytic results. The case of California is used to demonstrate that the integrated approach is a more effective way than either the single occupational or industrial analysis. The further application of this approach to data for the fifty states provides a general view of joint occupational and industrial development across the nation. This approach further links the occupational approach and the industrial development together by providing a new way to measure and identify the regional comparative difference to be able to implement more fruitful policy-making decisions.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".