Racial Evolution of an Urban Planet: Scenes From the North American Frontier
Bibliographic record
Abstract
In the Summer of 2020, as the latest coronavirus quickened its evolutionary journeys through the human mobilities of planetary urban systems, the research journal of the U.S. Department of Housing and Urban Development published an article by the world's most famous urban economist. Edward Glaeser's article, “The Closing of America's Urban Frontier,” celebrates the influential interpretation of U.S. history offered by Frederick Jackson Turner in a lecture delivered in Chicago in 1893, as part of Glaeser's advocacy of neoliberal, supply-side deregulated city-building as social policy. Yet Glaeser carefully evades the fundamental ethnoracial inequalities at the heart of Turner's frontier thesis, which were inseparable from the Social Darwinist hijacking of evolutionary thought that corrupted economics and other social sciences beginning in the late 19th century. In this paper, the Glaeser-Turner genealogy is used to interpret today's evolving materialities and discourses of race, class, identity, and urbanism. A mixed-methods blend of quantitative modeling and simple, descriptive online media analysis in the spirit of Robert Park's “Natural History of the Newspaper” is used to map the contours of competition, succession, and representation in a planetary urbanism that is now diagnosed as a new phase of “cognitive-cultural” capitalism. Cognitive-capitalist urbanism evolves along multiple semiotic frontiers of cosmopolitan diversity and multidimensional, intersectional hybridity – while valorizing performative competitive hierarchies that legitimate the reproduction of the structured inequalities of capital accumulation. Combinatoric expansion of the spatio-temporal reference points of identity and ancestry present daunting challenges to all who pursue equity or equality – requiring careful strategic confrontation of the meanings of neoliberal planetary human evolution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".