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Record W2070415196 · doi:10.1177/0096144208321875

Encountering and Overcoming Small-City Problems

2008· article· en· W2070415196 on OpenAlexaff
Kent Buse

Bibliographic record

VenueJournal of Urban History · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsLaurentian University
Fundersnot available
KeywordsEliteFeudalismPoliticsPort (circuit theory)DemocracyPopulationPosition (finance)AutonomyEconomyPolitical economyPolitical scienceSociologyLawEconomicsEngineering

Abstract

fetched live from OpenAlex

During the nineteenth century, Bremen enhanced its economic viability through a series of engineering feats, but struggled with the social problems brought on by urban growth. The most notable technical challenge was maintaining access to the North Sea and Atlantic via the silt-prone Weser River. Through the purchase of land for an outport (Bremerhaven) and a series of dredging operations headed by Ludwig Franzius, Bremen was able to preserve its position as a viable northern European port. But as the city's population grew, it proved less capable in dealing with the social and political challenges associated with urban growth. Its quasi-feudal political structure, which insulated elites from democratic pressures, made it difficult for the city to address housing and other social issues. Demands from the Social Democratic Party and other reformers ultimately undermined the city's elite and contributed to the city's loss of autonomy during the twentieth century.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0220.020
Scholarly communication0.0120.008
Open science0.0020.018
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0150.002

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 head0.076
GPT teacher head0.248
Teacher spread0.172 · 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 designQualitative
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

Citations2
Published2008
Admission routes1
Has abstractyes

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