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Regional Institutional Convergence? Reflections from the Baltimore Waterfront

2003· article· en· W2029882366 on OpenAlexaff
Peter Hall

Bibliographic record

VenueEconomic Geography · 2003
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAssertionInstitutional changeConvergence (economics)Diversity (politics)Port (circuit theory)PoliticsOptimal distinctiveness theoryFace (sociological concept)Process (computing)Political economyEconomic systemEconomicsSociologyPolitical scienceEconomic geographyPublic administrationLawEconomic growthSocial science

Abstract

fetched live from OpenAlex

Abstract: This article discusses the process of institutional change across regions in response to structural economic, social, political, and technological change. It accepts as a starting point the assertion that institutional differences between regions account, at least in part, for differences in regional development outcomes. This assertion raises the question of whether institutions in different locales will converge or diverge over time. The article explores this question through a case study of institutional changes associated with the process of containerization at the Port of Baltimore. Despite considerable pressure for convergent change in various formal institutions, specifically with respect to port pricing and terminal leasing policies, important elements of a common‐user approach to the operation of the port were maintained. This particular trajectory of institutional change is reflective of both the local political economy and the role of public officials in deliberating over formal institutional choices in the face of considerable uncertainty. The evidence supports a notion of institutional transformation in which regional institutional diversity, albeit in new forms, is maintained.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.012
Scholarly communication0.0080.005
Open science0.0020.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.023
GPT teacher head0.216
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations67
Published2003
Admission routes1
Has abstractyes

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