Most Nigerian Professors Struggle with poverty – Don

Professor Audi T. Giwa, Dean of the Faculty of Arts and former Dean of Students Affairs at Kaduna State University (KASU), has stated that most Nigerian professors are impoverished.

He noted that currently, very few professors can afford to drive cars due to inadequate remuneration and economic hardship.

Audi made the remarks following a presentation at a “Diversity in Science” project, an initiative by the Pharmafluence Education Advancement Network (PEAN) in collaboration with Kaduna State University.

He said most professors in Nigeria earn less than N500,000 monthly, yet society perceives them as rich men.

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“How many people do you know now who cannot afford to drive their own cars? These are rich people; they are not professors, because we are already poor. When you see a professor driving a car, they are among the specialized very few. Yet, society views us as big men,” he said.

“Quote me anywhere—no professor in this country earns more than N500,000 a month. Some earn as little as N300,000. Despite this, people view us as rich. If you claim not to have money, they react, This is the reality,” he added.

Audi further explained that the program aims to teach students about inclusiveness rather than diversity by focusing on commonalities rather than differences.

He criticized Nigerian leaders for exploiting societal differences for political gain and then uniting amongst themselves, leaving the general population in poverty.

He asserted that while diversity should benefit the nation, it currently does not, and even those who are semi-affluent are now experiencing poverty.

In his remarks, Pharmacist Kenneth Bitrus David, Founder and CEO of Pharmafluence Education Advancement Network (PEAN), mentioned that the seminar, funded by the Biochemical Society, aims to educate academics and students on the benefits of promoting equity, diversity, and inclusion (EDI) in their fields.

He emphasized the need for compassionate classrooms and measures to reduce both implicit and explicit biases in education and STEM (Science, Technology, Engineering, and Mathematics) fields.