Academic literature on the topic 'Southern Nigeria Survey'

Abstract Nigeria’s ethno religious plurality has persistently hindered cohesion among its many peoples. Thus, for over four decades, a debate has been ongoing over whether or not the Nigerian polity should be restructured. The present study drew from System Justification Theory to examine how the constituent groups in Nigeria are apparently kept united amidst perceptions of injustice from some of her ethnic groups. The paper also examined the extent to which the perceptions of distributive and procedural justice influence national identification. The study involved a survey of 230 federal university undergraduates. Participants responded to a scale on distributive and procedural justice beliefs as well as on measures of national identification. Results revealed that distributive and procedural justice beliefs have a significant influence on national group identification. Furthermore, respondents from the southern Nigeria showed strong identification with their ethnic groups but weak identification with the national group, while participants from northern Nigeria showed strong identification with the ethnic group and an equally strong identification with the national group. These findings suggest there is less national cohesion among Nigerian ethnic groups than is necessary for faster national development. Recommendations are therefore made on how national cohesion might be achieved in spite of cultural differences.

Pidgins and creoles are hybrid languages that evolve from situations of language contact (e.g. slave trade); creoles are traditionally regarded as pidgins that have acquired native speakers. Since the 1960s, the contemporary study of pidgins and creoles has grown from strength to strength, and has earned much-deserved academic recognition and respect in the field of linguistics, the subject area being now known as pidginistics and creolistics. Strangely, while some progress appears to have been made in the quest to define, classify and better understood their linguistic-structural dispositions (and possible applications), precious little study has been conducted on the anatomy of social attitudes toward such languages, in spite of the stigmatized statuses they traditionally suffer. To compound this point, equally relatively few language attitude studies have been conducted in Africa. This survey hopes to fill some of the current gap. Consequently, it was decided that a sociopsychological survey would be undertaken on Anglo-Nigerian Pidgin (ANP), a contact variety, which is said to have derived from initial contacts with Portuguese sailors in the 15^th century and the diverse ethnicities along the coastline of the geopolitical area now called 'Nigeria', and probably underwent processes of relexification/adlexification with intensified contacts with the British, especially in the 18^th century (Hancock, 1968). The findings on ANP appear to demonstrate that social attitudes are mainly based on pragmatic issues of formal and informal instrumentality, as would be the case with any other ('natural') language, and not on sociomoral considerations. The survey also throws up three possibly-viable hypotheses on language attitude orientations (Age of Contact Hypothesis; Source of Contact Hypothesis; and, Language Competence Hypothesis).

Introduction Nigeria has the highest malaria burden worldwide. The 2010 and 2015 Nigeria Malaria Indicator Surveys (NMIS) suggest an improvement in malaria indicators, with the North West zone lagging behind. This study aimed to identify the individual and household-level malaria determinants in north-west and southern Nigeria, using Rapid Diagnostic Testing (RDT) and microscopy for malaria diagnosis. Methods Data on 3,358 children aged 6-59 months from north-west and southern Nigeria from the 2015 NMIS was used. The two populations were compared using chi-square tests, and logistic regression analysis was done for determinants of malaria infection, based on RDT and microscopic malaria test results. Results Malaria prevalence by RDT in the north-west and south was 55.8% and 29.2%, respectively (37.0% and 14.9%, respectively by microscopy). In both populations, a higher age, positive RDT in an additional household member and rural residence increased the odds of malaria infection; while higher education of the head of household and greater household wealth lowered the odds of malaria infection. Household clustering of RDT-positive cases appeared to be stronger in the south compared to the north-west. There were no statistically significant differences between the results using RDT or microscopy. Conclusion Irrespective of the diagnostic tool used, malaria determinants were similar in north-west and southern Nigeria. However, poorer social circumstances were observed in the north-west, and may account for the delayed progress in malaria control in the region. There may be a need to intensify malaria control efforts, particularly in the north-west, while awaiting socio-economic development.

AbstractThis chapter was aimed at evaluating the responses of livestock to fluctuations in climate and the debilitating effect of livestock production on the environment. Survey of livestock stakeholders (farmers, researchers, marketers, and traders) was carried out in Sahel, Sudan, Northern Guinea Savannah, Southern Guinea Savannah, and Derived Savannah zones of Nigeria. In total, 362 respondents were interviewed between April and June 2020. The distribution of the respondents was 22 in Sahel, 57 in Sudan, 61 in Northern Guinea Savannah, 80 in Southern Guinea Savannah, and 106 in Derived Savannah. The respondents were purposively interviewed based on their engagement in livestock production, research or trading activities. Thirty-eight years’ climate data from 1982 to 2019 were obtained from Nigerian Metrological Agency, Abuja. Ilela, Kiyawa, and Sabon Gari were chosen to represent Sahel, Sudan, and Northern Guinea Savannah zone of Nigeria, respectively. The data contained precipitation, relative humidity, and minimum and maximum temperature. The temperature humidity index (THI) was calculated using the formula: THI = 0.8*T + RH*(T-14.4) + 46.4, where T = ambient or dry-bulb temperature in °C and RH=relative humidity expressed as a proportion. Three Machine Learning model were built to predict the monthly minimum temperature, maximum temperature, and relative humidity respectively based on information from the previous 11 months. The methodology adopted is to treat each prediction task as a supervised learning problem. This involves transforming the time series data into a feature-target dataset using autoregressive (AR) technique. The major component of the activities of livestock that was known to cause injury to the environment as depicted in this chapter was the production of greenhouse gases. From the respondents in this chapter, some adaptive measures were stated as having controlling and mitigating effect at reducing the effect of activities of livestock on the climate and the environment. The environment and climate on the other side of the dual pathway is also known to induce stress on livestock. The concept of crop-livestock integration system is advocated in this chapter as beneficial to livestock and environment in the short and long run. Based on the predictive model developed for temperature and relative humidity in a sample location (Ilela) using Machine Learning in this chapter, there is need for development of a web or standalone application that will be useable by Nigerian farmers, meteorological agencies, and extension organizations as climate fluctuation early warning system. Development of this predictive model needs to be expanded and made functional.

The aim of this study was to investigate the influence of faculty affiliation and teaching experience on the use of the Internet by faculty members in six first generation universities in Southern Nigeria. A total of 476 faculty members from nine faculties across the six universities participated in the study. The data for the study was collected by means of a questionnaire survey and this was deemed appropriate as it allowed the views of all the participants to be sought on a Likert-type scale options. The results of this study provide a number of insights: (a) the faculties of engineering, science and arts in that order were the foremost users of the Internet for instructional purposes; (b) the faculties of Education and Agriculture were the least experiences in the use of the Internet; and, (c) faculty members with less than five years teaching experience use the Internet more than older faculty members. Recommencati9on was made that universities in Nigeria should invest more in ICT facilities.

This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&D), academies of science, ministries of science and technology, policies, recognition of research, and participation in the Science Granting Councils Initiative (SGCI), the following countries demonstrate the highest commitment and political willingness to invest in science: Botswana, Ethiopia, Kenya, Senegal, South Africa, Tanzania, and Uganda. In addition to existing policies in Science, Technology and Innovation (STI), the following countries have made progress towards Open Data policies: Botswana, Kenya, Madagascar, Mauritius, South Africa and Uganda. Only two African countries (Kenya and South Africa) at this stage contribute 0.8% of its GDP (Gross Domestic Product) to R&D (Research and Development), which is the closest to the AU’s (African Union’s) suggested 1%. Countries such as Lesotho and Madagascar ranked as 0%, while the R&D expenditure for 24 African countries is unknown. In addition to this, science globally has become fully dependent on stable ICT (Information and Communication Technologies) infrastructure, which includes connectivity/bandwidth, high performance computing facilities and data services. This is especially applicable since countries globally are finding themselves in the midst of the 4th Industrial Revolution (4IR), which is not only “about” data, but which “is” data. According to an article1 by Alan Marcus (2015) (Senior Director, Head of Information Technology and Telecommunications Industries, World Economic Forum), “At its core, data represents a post-industrial opportunity. Its uses have unprecedented complexity, velocity and global reach. As digital communications become ubiquitous, data will rule in a world where nearly everyone and everything is connected in real time. That will require a highly reliable, secure and available infrastructure at its core, and innovation at the edge.” Every industry is affected as part of this revolution – also science. An important component of the digital transformation is “trust” – people must be able to trust that governments and all other industries (including the science sector), adequately handle and protect their data. This requires accountability on a global level, and digital industries must embrace the change and go for a higher standard of protection. “This will reassure consumers and citizens, benefitting the whole digital economy”, says Marcus. A stable and secure information and communication technologies (ICT) infrastructure – currently provided by the National Research and Education Networks (NRENs) – is key to advance collaboration in science. The AfricaConnect2 project (AfricaConnect (2012–2014) and AfricaConnect2 (2016–2018)) through establishing connectivity between National Research and Education Networks (NRENs), is planning to roll out AfricaConnect3 by the end of 2019. The concern however is that selected African governments (with the exception of a few countries such as South Africa, Mozambique, Ethiopia and others) have low awareness of the impact the Internet has today on all societal levels, how much ICT (and the 4th Industrial Revolution) have affected research, and the added value an NREN can bring to higher education and research in addressing the respective needs, which is far more complex than simply providing connectivity. Apart from more commitment and investment in R&D, African governments – to become and remain part of the 4th Industrial Revolution – have no option other than to acknowledge and commit to the role NRENs play in advancing science towards addressing the SDG (Sustainable Development Goals). For successful collaboration and direction, it is fundamental that policies within one country are aligned with one another. Alignment on continental level is crucial for the future Pan-African African Open Science Platform to be successful. Both the HIPSSA ((Harmonization of ICT Policies in Sub-Saharan Africa)3 project and WATRA (the West Africa Telecommunications Regulators Assembly)4, have made progress towards the regulation of the telecom sector, and in particular of bottlenecks which curb the development of competition among ISPs. A study under HIPSSA identified potential bottlenecks in access at an affordable price to the international capacity of submarine cables and suggested means and tools used by regulators to remedy them. Work on the recommended measures and making them operational continues in collaboration with WATRA. In addition to sufficient bandwidth and connectivity, high-performance computing facilities and services in support of data sharing are also required. The South African National Integrated Cyberinfrastructure System5 (NICIS) has made great progress in planning and setting up a cyberinfrastructure ecosystem in support of collaborative science and data sharing. The regional Southern African Development Community6 (SADC) Cyber-infrastructure Framework provides a valuable roadmap towards high-speed Internet, developing human capacity and skills in ICT technologies, high- performance computing and more. The following countries have been identified as having high-performance computing facilities, some as a result of the Square Kilometre Array7 (SKA) partnership: Botswana, Ghana, Kenya, Madagascar, Mozambique, Mauritius, Namibia, South Africa, Tunisia, and Zambia. More and more NRENs – especially the Level 6 NRENs 8 (Algeria, Egypt, Kenya, South Africa, and recently Zambia) – are exploring offering additional services; also in support of data sharing and transfer. The following NRENs already allow for running data-intensive applications and sharing of high-end computing assets, bio-modelling and computation on high-performance/ supercomputers: KENET (Kenya), TENET (South Africa), RENU (Uganda), ZAMREN (Zambia), EUN (Egypt) and ARN (Algeria). Fifteen higher education training institutions from eight African countries (Botswana, Benin, Kenya, Nigeria, Rwanda, South Africa, Sudan, and Tanzania) have been identified as offering formal courses on data science. In addition to formal degrees, a number of international short courses have been developed and free international online courses are also available as an option to build capacity and integrate as part of curricula. The small number of higher education or research intensive institutions offering data science is however insufficient, and there is a desperate need for more training in data science. The CODATA-RDA Schools of Research Data Science aim at addressing the continental need for foundational data skills across all disciplines, along with training conducted by The Carpentries 9 programme (specifically Data Carpentry 10 ). Thus far, CODATA-RDA schools in collaboration with AOSP, integrating content from Data Carpentry, were presented in Rwanda (in 2018), and during17-29 June 2019, in Ethiopia. Awareness regarding Open Science (including Open Data) is evident through the 12 Open Science-related Open Access/Open Data/Open Science declarations and agreements endorsed or signed by African governments; 200 Open Access journals from Africa registered on the Directory of Open Access Journals (DOAJ); 174 Open Access institutional research repositories registered on openDOAR (Directory of Open Access Repositories); 33 Open Access/Open Science policies registered on ROARMAP (Registry of Open Access Repository Mandates and Policies); 24 data repositories registered with the Registry of Data Repositories (re3data.org) (although the pilot project identified 66 research data repositories); and one data repository assigned the CoreTrustSeal. Although this is a start, far more needs to be done to align African data curation and research practices with global standards. Funding to conduct research remains a challenge. African researchers mostly fund their own research, and there are little incentives for them to make their research and accompanying data sets openly accessible. Funding and peer recognition, along with an enabling research environment conducive for research, are regarded as major incentives. The landscape report concludes with a number of concerns towards sharing research data openly, as well as challenges in terms of Open Data policy, ICT infrastructure supportive of data sharing, capacity building, lack of skills, and the need for incentives. Although great progress has been made in terms of Open Science and Open Data practices, more awareness needs to be created and further advocacy efforts are required for buy-in from African governments. A federated African Open Science Platform (AOSP) will not only encourage more collaboration among researchers in addressing the SDGs, but it will also benefit the many stakeholders identified as part of the pilot phase. The time is now, for governments in Africa, to acknowledge the important role of science in general, but specifically Open Science and Open Data, through developing and aligning the relevant policies, investing in an ICT infrastructure conducive for data sharing through committing funding to making NRENs financially sustainable, incentivising open research practices by scientists, and creating opportunities for more scientists and stakeholders across all disciplines to be trained in data management.