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Record W4280594398 · doi:10.33003/fjs-2022-0602-930

ANALYSING THE PATTERN AND URBAN PLANNING IMPLICATIONS OF SPRAWL ON QUALITY OF LIFE IN KADUNA METROPOLIS - NIGERIA

2022· article· en· W4280594398 on OpenAlexaboutno aff
Aliyu Hassan Ibrahim, Wisdom Chibuzor Odunze, Ndamadu Musa Farouk, Abubakar Adamu Liman

Bibliographic record

VenueFUDMA Journal of Sciences · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Urban sprawlGeographyPopulationGovernment (linguistics)SlumSocioeconomicsMultistage samplingEnvironmental planningUrban planningBusinessEconomic growthCivil engineeringEngineeringDemographySociologyStatisticsEconomicsArchaeology

Abstract

fetched live from OpenAlex

Various studies have highlighted different urban problems that have affected the quality of life of the urban dwellers in both developed and developing nations due to rapid socio - economic changes and increase in population. The aim of this study is to assess the perceived indicators of quality of life, so as to evolve strategy of upgrading the decayed urban communities. The multistage sampling method was adopted as a sampling technique. The following settlement were selected for the study, Down Quarters, Kurmin Gwari and Badarawa-Kwaru because of its slum like settlement. A total of 406 household’s heads/members were served with questionnaires, while 380 were returned and properly filled. Twelve (12) key informants were also interviewed in all the selected communities. The results show that more than three quarter of respondents get their water from hand dug well (M= 4.2151), and a little less than one quarter admitted to get water from Pipe borne, boreholes (M= 1.4272) and other sources. The study concluded that due to high population concentration of people, government could not provide the necessary amenities and services required by the teeming population therefore, the available ones were over stretched and became dilapidated and decay set in. The study recommends that the government of Kaduna state should embark on urban renewal which will prevent decay, clear areas bad areas, upgrade building, facilities and expand metropolis roads.

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)0.004
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 score0.062
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.115
GPT teacher head0.380
Teacher spread0.265 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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