New regional geographies of the world as practised by leading advanced producer service firms in 2010
Bibliographic record
Abstract
This paper reports a new type of world regionalisation based upon the location strategies of leading advanced producer service firms. To generate these ‘global practice’ regions, a principal components analysis of the office networks of 175 service firms across 138 cities is used to identify 10 common location strategies. These are interpreted as fuzzy (overlapping) and porous regional formations each consisting of two parts: a home‐region and a global‐outreach. The results indicate five overlapping pairs of regions: (i) intensive and extensive globalisations based upon the USA plus London (USAL); (ii) Americas and Latin America regions; (iii) Pacific Asia and China regions; (iv) Europe and Scandinavia regions; and (v) Australasian and Canadian ‘Commonwealth’ regions. All regions have worldwide global‐outreaches but they differ significantly in their respective sizes and importance. Discussion of these findings elaborates upon two key points: first, globalisation is not a ‘blanket’ process creating a homogeneous world, and second, the resulting fuzzy and porous regionalisation counters the traditional ‘territorialist’ regional geographies that can provide a framework for global conflict with a more complex geography of multiple global integrations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".