Bibliographic record
Abstract
City and Country: an Interdisciplinary Collection: 1. Editor's Introduction: Laurence S. Moss. Part I: Historical Perspectives on the Agglomeration Approach to Economic Growth: 1. Henry George and Classical Growth Theory: A Significant Contribution to Modeling Scale Economies : John Whitaker. 2. Modeling Agglomeration and Dispersion in City and Country Gunnar Myrdal, Francois Perroux, and the New Economic Geography: Stephen J. Meardon. 3. City and Country: Lessons from European Economic Thought: Jurgen G. Backhaus Gerrit Meijer. 4. Making the Country Work for the City: Von Thunen's Ideas in Geography, Agricultural Economics and the Sociology of Agriculture: Daniel Block, E. Melanie DuPuis. Part II: New Research on Size, Geography, Specialization and Productivity: 1. Agglomeration and Congestionin the Economics of Ideas and Technological Change: Norman Sedgley Bruce Elmslie. 2. Zipf's Law for Cities and Beyond: The Case of Denmark: Thorbjorn Knudsen. 3. The Structure of Sprawl: Identifying and Characterizing Employment Centers in Polycentric Metropolitan Areas: Nathan B. Anderson, William T. Bogart. 4. Edge Cities and the Viability of Metropolitan Economies: Contributions to Flexibility and External Linkages by New Urban Service Environments: David L. McKee Yosra A. McKee. 5. Manufacturing and Rural Economies in the United States: The Role of Nondurable Producers, Labor Costs and State Taxes: Mark Jelavich. Part III: Case Studies: Land Value Taxation and Real Estate Development: 1. Value Capture as a Policy Tool in Transportation Economics: An Exploration in Public Finance in the Tradition of Henry George: H. William Batt. 2. Coordinating Opposite Approaches to Managing Urban Growth and Curbing Sprawl: A Synthesis: Thomas L. Daniels. 3. Leapfrogging, Urban Sprawl, and Growth Management: Phoenix, 1950 - 2000: Carol E. Heim. 4. A City without Slums: Urban Renewal, Public Housing, and Downtown Revitalization in Kansas City, Missouri: Kevin Fox Gotham. 5. A City Divided by Political Philosophies: Residential Development in a Bi-Provincial City in Canada: Gura Bhargava. Part IV: The Transformation of the City in the 21st Century: 1. International Sister-Cities: Bridging the Global-Local Divide: Rolf D. Cremer Anne de Bruin Ann Dupuis. 2. The Completely Decentralized City: The Case for Benefits Based Public Finance: Fed E. Foldvary. Index.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.146 | 0.044 |
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".