Cities and visitors : regulating people, markets, and city space
Bibliographic record
Abstract
List of Illustrations vii List of Tables ix List of Contributors xi Series Editorsa Preface xv Preface xvi Introduction 1 Susan S. Fainstein, Lily M. Hoffman, and Dennis R. Judd Part I: Regulating Visitors 21 1 Visitors and the Spatial Ecology of the City Dennis R. Judd 23 2 Cities, Security, and Visitors: Managing Mega--Events in France Sophie Body--Gendrot 39 3 Sociological Theories of Tourism and Regulation Theory Nicolo Costa and Guido Martinotti 53 Part II: Regulating City Space 73 4 Amsterdam: It's All in the Mix Pieter Terhorst, Jacques van de Ven, and Leon Deben 75 5 Revalorizing the Inner City: Tourism and Regulation in Harlem Lily M. Hoffman 91 6 Barcelona: Governing Coalitions, Visitors, and the Changing City Center Marisol Garcia and Nuria Claver 113 7 The Evolution of Australian Tourism Urbanization Patrick Mullins 126 Part III: Regulating Labor Markets 143 8 Regulating Hospitality: Tourism Workers in New York and Los Angeles David L. Gladstone and Susan S. Fainstein 145 9 Shaping the Tourism Labor Market in Montreal Marc V. Levine 167 Part IV: Regulating the Tourism Industry 185 10 Mexico: Tensions in the Fordist Model of Tourism Development Daniel Hiernaux--Nicolas 187 11 The New Berlin: Marketing the City of Dreams Hartmut Haussermann and Claire Colomb 200 12 Museums as Flagships of Urban Development Chris Hamnett and Noam Shoval 219 Part V: Conclusion 237 13 Making Theoretical Sense of Tourism Susan S. Fainstein, Lily M. Hoffman, and Dennis R. Judd 239 Index 254
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".