Skip to main navigation Skip to search Skip to main content
No photo of Pretty Karibo

Pretty Karibo

Miss

Former affiliations
20262026

Research activity per year

Personal profile

Research

Pretty Karibo is a PhD candidate in Sociology and Social Policy at Bangor University, Wales, and a Fellow of the Higher Education Academy. Her research specialises in computational policy analysis, with particular interests in machine learning, policy evaluation, land valuation and socioeconomic outcomes. Her doctoral work applies predictive modelling and simulation methods to study how policy and fiscal conditions are associated with human development outcomes across developing economies. She is a co-author of the Welsh Government report Testing Land Valuation Methodologies (2026), for which she led the computational framework, GIS analysis, spatial data engineering and digital platform development. She holds an MA in Social Policy with Distinction from Bangor University and an MSc in Gender and Women Development Studies from the University of Port Harcourt, completed with an excellent CGPA of 4.62/5.00. She has teaching experience in social policy, research methods and data analytics, and previously supported policy and equality work at Gwynedd Council. She is also a member of the Social Policy Association.

Contact Info

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Fingerprint

Dive into the research topics where Pretty Karibo is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
  • 1 Similar Profiles

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or