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Record W2258776321 · doi:10.5539/jsd.v9n1p77

Harnessing the Tension from Context-duality in Historic Urban Environment

2016· article· en· W2258776321 on OpenAlexvenueno aff
Ejeng Ukabi

Bibliographic record

VenueJournal of Sustainable Development · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Divergence (linguistics)Process (computing)Argument (complex analysis)SustainabilityConvergence (economics)Limit (mathematics)Tension (geology)Bridge (graph theory)Architectural engineeringComputer scienceSociologyCivil engineeringGeographyEngineeringArchaeologyMathematicsEconomicsEcology

Abstract

fetched live from OpenAlex

The quest for improvement and upgrading of the historic urban environment through coexisting historical context and new context had introduced tension over the previous years. The resultant flows have jeopardized the harmonious layers of historical settings. The concept of conservation that provides the needed bridge between the forces in many cases implemented exhibits a no consideration of the three polarities that controls historic areas. The aftermath shows up in two ways. At one end is convergence and divergence at the other but the emphasis of this paper focuses on investigating what happens in historic urban environments when annex developments exceed historic limits? Historic Limit (HL) is the hidden benchmark and maximum point of the historic urban environment at which the forces produced by the two contexts coexist elastically. In order to answer the generated question, a literature review of the keywords that constitutes the topic is explored. The ideas of Warren John on ‘interaction’ and that of Getty Conservation Institute on ‘relationship’ that happens in the built above environment will buttress the argument. A model that represents the correlation of the two contexts is developed to simplify the overall intentions of the essay. Another technique is the selection of two composite annex cases to validate the targeted objectives. The article is concluded by recommending that conservation schemes in historic urban landscapes should adopt consensus design strategy for tackling context tension. As a sure way of sustainably welcoming the voices of the community in the process before implementation of the 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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.207
Teacher spread0.153 · 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 designNot applicable
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

Citations4
Published2016
Admission routes1
Has abstractyes

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