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Record W3084374871 · doi:10.24043/isj.349

Urban growth and cultural identity; fractures and imbalances in heritage values: A case study of the island of Saint-Louis, Senegal

2016· article· en· W3084374871 on OpenAlexaffvenue
Lucía Martínez Quintana, Eduardo Cáceres-Morales

Bibliographic record

VenueIsland Studies Journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsSAINTContext (archaeology)MainlandGeographyPrestigePoliticsCultural heritageCapital (architecture)Cultural heritage managementEconomyTypologyMainland ChinaHistoryEthnologyPolitical scienceArchaeologyLawChina

Abstract

fetched live from OpenAlex

The island of Saint-Louis of Senegal was awarded the status of world heritage site by UNESCO in 2000 as an “outstanding example” of urban heritage. This island city comes with a unique heritage: development planning that combines a strong historical French influence with a gridiron urban morphology and building typology. The island must be interpreted within its total territorial context that includes both the island of Sor (on the mainland) and La Langue de la Barberie, a sandy barrier that separates the mouth of the river from the sea. The city of Saint-Louis itself has grown enormously and haphazardly from the latter part of the 20th century: it is now the fourth most populous city in Senegal. At present, the city is undergoing a serious period of decline and recession due, in part, to the overriding influence of the capital, Dakar, and the centralized political forces in the country. This article looks at the key morphological and functional reasons behind the development and evolution of the island of Saint-Louis and that persist in the present context, with justifications for the deep-rooted heritage values that maintain its prestige as a World Heritage Site.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.270
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.027
GPT teacher head0.316
Teacher spread0.288 · 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 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

Citations5
Published2016
Admission routes2
Has abstractyes

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