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Record W3216126941 · doi:10.18280/ijsdp.160605

Sustainable Urban Development for Costal City Case Study: Bourg El-Bourols City

2021· article· en· W3216126941 on OpenAlexvenueno aff
Amany Ragheb, Haithem El Sharnouby

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsUrban planningEnvironmental planningSustainable developmentPossession (linguistics)GeographyRegional scienceBusinessEnvironmental resource managementCivil engineeringPolitical scienceEngineeringEnvironmental science

Abstract

fetched live from OpenAlex

Comprehensive urban development varies from place to place according to the different natural environment, unplanned urban development on coastal cities led to an urban disruption and random possession of lands, Burj Al-Burullus is a coastal city with high environmental sensitivity and has many environmental, social, and cultural systems that qualify it to be a development area with a distinct character. The challenges of urban development represent the biggest challenge to development in the region. Despite the presence of many development plans in the region, there is no clear methodology that considers the resources and the distinct potentials of these areas to make use of them in solving the problems that hinder development. The research presents an attempt to reach a mechanism through which sustainable urban development can be achieved in all economic, social, and demographic aspects. In addition, it contributes to formulating a vision and developing a strategy to achieve sustainable urban development, with the participation of economic institutions in a way that stimulates these institutions to invest. The research studies and evaluates the current reality of Burj Al-Burullus city using GIS in terms of the characteristics and activities of the city and explores its developmental reality. The research attempts to find appropriate urban solutions to overcome these urban challenges and develop plans to be used as a link between the challenges and development results and to be followed in the development of the region and similar areas.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.046
GPT teacher head0.335
Teacher spread0.289 · 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.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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