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Record W4415720717 · doi:10.11113/umran2025.12n3.788

Balancing Infrastructural Development and Social Welfare: An Islamic Perspective on the Ibadan Circular Road Project Controversy

2025· article· W4415720717 on OpenAlexaff
Ridwan Olamilekan Mustapha, Yakub Olawale Abdulwahab

Bibliographic record

VenueUMRAN - International Journal of Islamic and Civilizational Studies · 2025
Typearticle
Language
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGovernment (linguistics)IslamState (computer science)Perspective (graphical)Corporate governanceBalance (ability)Qualitative research

Abstract

fetched live from OpenAlex

This paper addresses the controversy on the Ibadan Circular Road (ICR) project in Oyo State, Nigeria, particularly its impact on residents displaced in six local government areas: Ido, Akinyele, Egbeda, Ona-Ara, Lagelu, and Oluyole. While the project aims at urban renewal and benefits for residents and commuters, many argue that the government's approach has imposed hardship on those displaced, leading to allegations of unfair practices. The study examines the issue through the lens of Islamic governance and urban development systems, suggesting that contemporary leaders can learn to balance infrastructure development with social justice. Using qualitative case study methodology, including government documents and surveys of 60 out of the displaced residents, the findings indicate that at least 500 individuals have become homeless due to government-initiated demolition. The paper recommends that the state government should have adopted Caliph Umar’s principles to ensure a balance between development and social welfare, setting a positive precedent for future projects.

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)0.004
metaresearch head score (Gemma)0.002
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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.027
Scholarly communication0.0070.004
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.323
Teacher spread0.297 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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