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Record W4310870234 · doi:10.18280/ijsdp.170734

Urban Landscape Design for Riverfronts in Iraqi Cities a Comparative Study Between Local and Regional Legislation

2022· article· en· W4310870234 on OpenAlexvenueno aff
Ekhlas Nasraldeen Alansari, Ahmed Yousif Alomary

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2022
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
FundersUniversity of Mosul
KeywordsLegislationEnvironmental planningPaceLegislatureUrban planningBusinessEnvironmental resource managementEnvironmental protectionGeographyPolitical scienceCivil engineeringLawEngineeringEconomics

Abstract

fetched live from OpenAlex

Iraq has multiple water resources, so it urgently needs legislation to develop its river bank and benefit from its water resources. The purpose of this study is to investigate the shortcomings in the lack of development of the urban landscape of riverfronts in Iraqi cities by reviewing the legislative aspect of the laws regulating them, which are supposed to improve the quality of life for its citizens and achieve better environmental, social, economic and urban exploitation. This research was carried out using a qualitative approach, by analyzing the content of legislation and guidelines for urban landscapes for waterfronts in regional countries, finding urban design principles in them, and comparing them with the current Iraqi laws through the checklist. The results show that there are shortcomings in the Iraqi legislation for riverfronts and that it does not keep pace with the changes taking place in the world. The results were used to present proposals for the development of urban landscape legislation for the riverfront in Iraqi cities, in line with their social, economic and environmental conditions.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.048
GPT teacher head0.270
Teacher spread0.222 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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