Who Wants to Go Where? Regional Variations in Emigration Intention in Nigeria

There has been an increase in the number of Nigerians desperately leaving the country. In the absence of accurate data on the rate of actual emigration, this study investigated emigration intention in Nigeria, and how it varies between northern and southern Nigeria – two regions with perennial sociocultural differences that have been neglected in migration research. The study also investigated the factors associated with emigration intention. It utilized secondary data from the Afrobarometer survey, including 1,600 Nigerian adults aged 18 and above. Logistic regression models were fitted to address the study objectives. The study found that the emigration intention rate in Nigeria was 35.5%, but it varied from 30.3% in the north to 40.3% in the south. The rate ranged from 26% in the north-east to 46.4% in the south-eastern part of the country. The most preferred destination for northern Nigerians was another country in Africa (32.4%), but it was North America for southerners (43.2%). At the multivariate level, the study found that living in the south, being educated, using the internet frequently, having tolerance for homosexuals, and participating in politics increased the likelihood of emigration intention. However, being old, employed and having religious tolerance reduced the odds of emigration intention. The regional models revealed notable differences in the influence of age, education, employment, tolerance, and political participation. The study discusses the implications of the findings

Small Scale Enterprisesand the Economic Siamese of Nigeria: Growth-Barrier Chain Analysis

This study investigated the SME growth-barrier chain in Nigeria. A target population of 39,600 was sampled using Taro Yamane method to achieve the surveyed 396 respondents. A well structured questionnaire was administered to collect the data. Percentage, descriptive, Likert analysis and regression analysis were used to explain the nature of the SME growth-barrier chain in Nigeria. Results of the study reveal that barrier factors have been influencing SMEs growth in Nigeria, and that the most significant among the barrier factors are entrepreneurial skill, irregular power supply and lack of business strategy. This study is limited by sample size and selection of SMEs at their clustered areas, and therefore may not be generalized to other sectors and countries. The study concludes that these factors cause epileptic growth or sudden death of SMEs in Nigeria. The study recommends that the government should engage in intervention programmes, and also ensure regular power supply in Nigeria. In addition, SME owner-managers should adopt and implement business strategies in their business environment. Keywords: SMEs growth. Barrier factors, employment, Business Strategy, Entrepreneurial Skil

MasakhaNEWS: News Topic Classification for African languages

African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. named entity recognition and machine translation) have standardized benchmark datasets covering several geographical and typologically-diverse African languages. In this paper, we develop MasakhaNEWS -- a new benchmark dataset for news topic classification covering 16 languages widely spoken in Africa. We provide an evaluation of baseline models by training classical machine learning models and fine-tuning several language models. Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API). Our evaluation in zero-shot setting shows the potential of prompting ChatGPT for news topic classification in low-resource African languages, achieving an average performance of 70 F1 points without leveraging additional supervision like MAD-X. In few-shot setting, we show that with as little as 10 examples per label, we achieved more than 90\% (i.e. 86.0 F1 points) of the performance of full supervised training (92.6 F1 points) leveraging the PET approach.Comment: Accepted to IJCNLP-AACL 2023 (main conference

AfriQA:Cross-lingual Open-Retrieval Question Answering for African Languages

African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingual open-retrieval question answering (XOR QA) systems -- those that retrieve answer content from other languages while serving people in their native language -- offer a means of filling this gap. To this end, we create AfriQA, the first cross-lingual QA dataset with a focus on African languages. AfriQA includes 12,000+ XOR QA examples across 10 African languages. While previous datasets have focused primarily on languages where cross-lingual QA augments coverage from the target language, AfriQA focuses on languages where cross-lingual answer content is the only high-coverage source of answer content. Because of this, we argue that African languages are one of the most important and realistic use cases for XOR QA. Our experiments demonstrate the poor performance of automatic translation and multilingual retrieval methods. Overall, AfriQA proves challenging for state-of-the-art QA models. We hope that the dataset enables the development of more equitable QA technology

MasakhaNEWS:News Topic Classification for African languages

African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. named entity recognition and machine translation) have standardized benchmark datasets covering several geographical and typologically-diverse African languages. In this paper, we develop MasakhaNEWS -- a new benchmark dataset for news topic classification covering 16 languages widely spoken in Africa. We provide an evaluation of baseline models by training classical machine learning models and fine-tuning several language models. Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API). Our evaluation in zero-shot setting shows the potential of prompting ChatGPT for news topic classification in low-resource African languages, achieving an average performance of 70 F1 points without leveraging additional supervision like MAD-X. In few-shot setting, we show that with as little as 10 examples per label, we achieved more than 90\% (i.e. 86.0 F1 points) of the performance of full supervised training (92.6 F1 points) leveraging the PET approach

Student on-campus housing at bursting point

undefine

Predictors and consequences of early sexual debut among students in tertiary institutions in Lagos metropolis, Nigeria

This study investigated the factors associated with early sexual debut, consensual sexual debut and multiple sexual partners in tertiary institutions in Lagos Metropolis, Nigeria. The study adopted a cross-sectional survey design with a proportional sampling method. Structured questionnaire was used to elicit information from respondents. Four hundred and thirty-three questionnaires were deemed eligible for data analysis. Chi-square, t-test and binary logistic regression were utilised to analyse the data. It was found that respondents who attended private secondary schools were more likely to have early sexual debut (X2= 3.076; p<0.05). There was no significant difference in the age at sexual debut for respondents from nuclear and extended families (M.D = -0.377). Females were less likely to experience consensual sexual debut than their male counterparts (OR=0.469; p<0.01). Also, early sexual debut influenced exposure to multiple sexual partners- those who delayed sex till age 22 were the least likely to be exposed (OR= 0.056; p<0.001). Adequate sex education of young people-beginning at early years- before their sexual debut is important for improved sexual health. Keywords: Sexual debut, multiple sexual partners, consensual sex, undergraduates; family type; Nigeria   Cette étude a examiné les facteurs associés aux débuts sexuels précoces, aux débuts sexuels consensuels et aux partenaires sexuels multiples dans des établissements tertiaires de Lagos Metropolis, au Nigéria. L'étude a adopté un plan d'enquête transversal avec une méthode d'échantillonnage proportionnel. Un questionnaire structuré a été utilisé pour obtenir des informations auprès des répondants. Quatre cent trente-trois questionnaires ont été jugés éligibles pour l'analyse des données. Le chi carré, le test t et la régression logistique binaire ont été utilisés pour analyser les données. Il a été constaté que les répondants qui fréquentaient des écoles secondaires privées étaient plus susceptibles d'avoir des débuts sexuels précoces (X2 = 3,076; p <0,05). Il n'y avait pas de différence significative d'âge au début des rapports sexuels pour les répondants issus de familles nucléaires et élargies (M.D = -0,377). Les femmes étaient moins susceptibles d'avoir des débuts sexuels consensuels que leurs homologues masculins (OR = 0,469; p <0,01). En outre, les débuts sexuels précoces ont influencé l'exposition à plusieurs partenaires sexuels - ceux qui ont retardé les rapports sexuels jusqu'à l'âge de 22 ans étaient les moins susceptibles d'être exposés (OR = 0,056; p <0,001). Une éducation sexuelle adéquate des jeunes - dès les premières années - avant leurs débuts sexuels est importante pour une meilleure santé sexuelle. Mots-clés: Débuts sexuels, partenaires sexuels multiples, rapports sexuels consensuels, étudiants de premier cycle; type de famille; Nigeri

Gambling in Transition: Assessing Youth Narratives of Gambling in Nigeria

Nigeria has witnessed some significant changes in gambling which have resulted in more people becoming interested in the activity. In an attempt to increase participation, bookmakers have introduced a variety of innovations. Literature has established that this increased participation is intergenerational, cross-cultural, and inter-religious. Particularly among Nigerian youth, participation in gambling cuts across all age groups, socioeconomic status, and gender. Both financial and social rewards have been identified as reasons why many youths gamble. Through a qualitative lens, this study investigates how the dynamics of gambling in recent times have affected the biographies of youth within a relatively deprived socio-economic locality in Kwara State, Nigeria. Thirty young gamblers between the ages of 15 and 29 were engaged in a semi-structured interview session. Drawing from the meaning of ‘youth’ from a sociological lexicon, one can advance this unique narrative of the transitions in gambling activities which can occur as a result of the youths’ biographies and socio-economic status. Nigerian youth adopt three specific gambling types as a coping strategy in the face of a crisis ridden socio-economic structure characterised by poverty, and unemployment. As such, gambling has become a normative activity experimented by the youth to survive the harsh economic conditions. This study therefore argues the need to situate the discourse of youth gambling within the social, cultural, and economic context in which they are located in Nigeria. In addition, the authors provide a framework for understanding the complexity of youth gambling in Nigeria

Tweets on COVID-19 Pandemic in Nigeria: Lesson Learned

Summary: Aim & Scope: Communication and Agenda Setting in the Post COVID-19 Era. Purpose of the Study: This study seeks to show the ways Twitter has been used to track the early pandemic detection, to monitor the dissemination of information and to explore the public awareness and attitudes of Nigeria. This is done in order to address the public health surveillance challenges in Nigeria to better inform future efforts to leverage Twitter's public health potential. Problem Addressed: Developing countries, including Nigeria perpetually finds it difficult to proactively and actively monitor disease outbreaks especially in its early stages due to the poor quality of manpower, scarcity of public health data and absence of automated surveillance. Methodology: From February 20 - May 6, 2020, English Tweets mentioning COVID-19 and related keywords were collected in 11 batches via NCapture™ plugin available on Google Chrome. The analysis includes a time series analysis to track the distribution of data and content analysis to analyze the knowledge and attitudes of Nigerians. Results: A total of 67,989 tweets (1,484 unique and 66,505 retweets) citing COVID-19 and related keywords were returned. The Tweets started to emerge on Twitter earlier to the first confirmed case in Nigeria, while maintaining a dangling-upward movement. Matters arising from the tweets include dearth of information on COVID-19, and optimism among others. Owing to the study of a specific dataset of Twitter collected at the earliest stage of the current pandemic in Nigeria, the results provide insight into the intersection of social media and public health surveillance. Recommendations: Results show how helpful Twitter is to educate education in public health. Health organisations and the government may benefit from paying attention to the both amusing and emotional contents from the twitter community in order to formulate a viable policy for treatment and control