Siting Federal Capitals: The American and German Debates
Bibliographic record
Abstract
The journal Foreign Affairs marked the fiftieth anniversary of the Berlin Airlift with a series of articles on the city's past and future. In one, Christoph Bertram argued that while national politics no longer requires a capital, national political culture does. In another article, Gordon A. Craig observed that the prestige of a great nation depends on how it promotes the arts and sciences and attends to its capital. By “capital,” both Bertram and Craig mean much more than just “seat of government,” a place limited to the governing function. A capital is a seat not only of government, but also of culture and business, and even of the social elite. A capital is a multidimensional reflection of national identity and a repository of a nation's memory. While a seat of government can evolve into a capital - as the case of Washington demonstrates - the distinction can remain quite clear. The Netherlands' seat of government is The Hague but its capital is bustling, commercial Amsterdam, the national cultural center. Canberra, Ottawa, New Delhi, and Brasilia are only seats of government; important political decisions are made in these cities, and they receive little public attention except for such decisions. London and Paris, on the other hand, are capitals in the true sense of the word. For several centuries, they have been hubs of urban, political, commercial, and cultural development. What do the histories of Berlin and Washington tell us about this distinction?
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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 | 0.003 | 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 | 0.015 | 0.018 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".