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Record W4397294430 · doi:10.58709/niujhu.v8i4.1726

Effects of Sustainable Development Goals on Poverty Reduction, Water and Sanitation in Nigeria during the Pandemic Era

2023· article· en· W4397294430 on OpenAlexaff
Patricia Ibeme, Julius Taiwo Abimboye, Chinenye Atuegbu, Chinedu Ibeme, Arinze Ibeme

Bibliographic record

VenueNIU journal of humanities. · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSanitationPovertyEmpowermentNigeriansEconomic growthSustainable developmentCash transfersGovernment (linguistics)BusinessDevelopment economicsPolitical scienceEconomicsEngineering

Abstract

fetched live from OpenAlex

This paper examines the profound effect of Sustainable Development Goals (SDGs) on poverty reduction, water and sanitation in the context of the pandemic era in Nigeria. As high-profile academia and bureaucrats seek to navigate the intricate landscape of development policy and practice, understanding the interplay between the SDGs, pandemic challenges, and Nigeria's socio-economic fabric becomes paramount. The study adopted documentary research design method through a comprehensive review of existing literature and empirical analysis. Findings from the study show that, good strides have been made in the domestication process of the SDGs in Nigeria. Nigeria has developed its home-grown ‘Integrated Sustainable Development Goals (SDG Model) the model includes; empowerment, conditional cash transfers and vocational training, trader-moni, Market-moni, ANCOR borrowers programme of CBN. Finding from the study shows that between 2015–2021, over 10.5 million Nigerians were lifted out of poverty through empowerment, conditional cash transfers and vocational training, President Muhammadu Buhari revealed that, government has lifted 10.5 million Nigerians out of poverty in the last two years. Buhari revealed that, those lifted out of poverty include farmers, artisans, market women, and small-scale traders. Finding from the study shows that, Seven hundred thirty-two (732) waters and sanitation related projects were executed, while Finding from the study shows that, 616 classrooms and other educational facilities were built or renovated. It was further showing that, a key challenge confronting the country has to do with Out-of- School-Children, a demographic challenge that relates to interplay between employment (SDG-8), education (SDG-4), poverty (SDG-1) and the digital economy (SDG-17). The study recommends thatThe government should encourage Sustainable Development Initiatives. The government should integrate sustainable development practices into policies and initiatives related to poverty reduction, water, and sanitation. Promote the use of renewable energy, encourage sustainable agricultural practices, and prioritize the conservation of natural resources. The government should support the development of eco-friendly technologies and solutions to minimize the environmental impact of development efforts. The government should expand social protection programs to support vulnerable populations, including the poor, elderly, and informal workers, by providing cash transfers, food assistance, and healthcare services. Implement targeted programs that reach those most in need, using technology and data to identify and assist marginalized communities Keywords: Sustainable Development Goals, United Nations, Covid-19 pandemic, poverty reduction, water and sanitation, Nigeria.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.196

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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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
Published2023
Admission routes1
Has abstractyes

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