Urban Specialisation; from Sectoral to Functional
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The comparative advantage of many cities is based on their efficiency in the production of 'functions', e.g., business services such as finance, law, engineering, or similar functions that are used by firms in a wide range of sectors. Firms that use these functions may choose to source them locally, or to purchase them from other cities. The former case gives rise to cities developing a pattern of sectoral specialization, and the latter a pattern of functional specialization. A two-city country trades with the larger world, and workers within the country are mobile between the two cities. Productivity in a given function varies across cities, giving rise to urban comparative advantage. This may be due to exogenous technological differences (Ricardian) or to city-and function-specific scale economies. Sectors differ in the intensity with which they use different functions, giving rise to a pattern of sectoral and functional specialisation. We generate a number of economic insights, and examine the model's predictions empirically over a 20-30year period for US states. As geographic fragmentation costs fall, both our theory and empirical analysis show that sector concentration and regional specialization fall for sectors and rise for functions (occupations).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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