Globalization from Below: The Ranking of Global Immigrant Cities
Bibliographic record
Abstract
Immigration to major cities is an important dimension of cultural globalization, one that has been largely ignored in the global cities literature. Rates of immigration to major world cities are an important indicator of global city status and should be included in determining urban hierarchy indexes. Our study considers immigration in more than 100 metropolitan areas, using data from national censuses from more than 50 countries. We rank major cities of immigration and compare them to well‐known global city hierarchies. Using immigration data, we create an urban immigrant index. The index considers four factors of immigration: (1) the percentage of foreign‐born, (2) the total number of foreign‐born, (3) the diversity of the foreign‐born stock, and (4) whether immigrants are from neighboring countries or non‐neighboring countries. This is the first time that an international urban immigrant data set and index have been created. The study explains the empirical challenge of acquiring comparable international metropolitan data and the limits of this research. Some of the cities that rank highly in the index are commonly cited as world cities (London, New York and Frankfurt); others such as Toronto, Amsterdam and Dubai seldom appear so highly ranked. L’Immigration vers les grandes villes est une dimension importante de la mondialisation culturelle, dimension largement ignorée dans la littérature sur les villes planétaires. Les taux d’immigration vers les grandes villes mondiales sont un indicateur significatif du statut de ville planétaire et devraient être pris en compte pour établir des répertoires de hiérarchie urbaine. Cette étude, qui couvre l’immigration dans plus de cent zones métropolitaines, utilise les données de recensements nationaux provenant de plus de 50 pays. Elle classe les principales villes d’immigration et les compare aux hiérarchies de villes planétaires reconnues. A partir des données sur l’immigration, est créé un répertoire des immigrants urbains, lequel se réfère à quatre facteurs d’immigration: (1) le pourcentage néà l’étranger, (2) l’effectif total néà l’étranger, (3) la diversité de la population née à l’étranger et (4) si les migrants viennent de pays voisins ou non. C’est la première fois qu’un fichier de données et un répertoire d’immigrants urbains internationaux sont créés. L’étude expose le défi empirique pour récupérer des données métropolitaines internationales comparables, ainsi que les limites de cette recherche. Certaines des villes placées en tête du répertoire sont fréquemment citées comme villes mondiales (Londres, New York et Frankfort), d’autres comme Toronto, Amsterdam et Dubaï apparaissent rarement à ce niveau de classement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".