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Record W2770026469 · doi:10.4324/9781315545837

The Political Economy of Capital Cities

2017· book· en· W2770026469 on OpenAlexaboutno aff
Heike Mayer, Fritz Sager, David Kaufmann, Martin Warland

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsCapital (architecture)EconomyEconomic systemEconomicsPolitical economyPolitical scienceGeographyArchaeology

Abstract

fetched live from OpenAlex

Capital cities that are not the dominant economic centers of their nations – so-called ‘secondary capital cities’ (SCCs) – tend to be overlooked in the fields of economic geography and political science. Yet, capital cities play an important role in shaping the political, economic, social and cultural identity of a nation. As the seat of power and decision-making, capital cities represent a nation’s identity not only through their symbolic architecture but also through their economies and through the ways in which they position themselves in national urban networks. The Political Economy of Capital Cities aims to address this gap by presenting the dynamics that influence policy and economic development in four in-depth case studies examining the SCCs of Bern, Ottawa, The Hague and Washington, D.C. In contrast to traditional accounts of capital cities, this book conceptualizes the modern national capital as an innovation-driven economy influenced by national, local and regional actors. Nationally, overarching trends in the direction of outsourcing and tertiarization of the public-sector influence the fate of capital cities. Regional policymakers in all four of the highlighted cities leverage the presence of national government agencies and stimulate the economy by way of various locational policy strategies. While accounting for their secondary status, this book illustrates how capital-city actors such as firms, national, regional and local governments, policymakers and planning practitioners are keenly aware of the unique status of their city. The conclusion provides practical recommendations for policymakers in SCCs and highlights ways in which they can help to promote economic development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.652
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.290
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations17
Published2017
Admission routes1
Has abstractyes

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