Culture, Globalization, and Social Cohesion: Towards a De-territorialized, Global Fluids Model
Bibliographic record
Abstract
To conceptualize the interrelationship among culture, social cohesion, and globalization, this paper uses Urry's three "social topographies" of space: region, network, and fluids. Fluids describe the de-territorialized movement of people, information, objects, money, and images across regions in an undirected and non-linear fashion. They are characteristically emergent, hybridized, urban, and cosmopolitan. Drawing upon Appadurai's five dimensions of global cultural flows (ethnoscapes, technoscapes, finanscapes, mediascapes, ideoscapes) and using examples from Britain, the U.S., and Canada, the paper argues for greater research and policy attention to the processes whereby transnational and hybrid identities are forged in cities. It concludes by introducing some empirical indicators of cosmopolitanization that represent a starting point for further research into the linkages between global cultural fluids and social cohesion.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".