Bibliographic record
Abstract
Her Excellency Professor Judi Wangalwa Wakhungu EGH was appointed Ambassador of Kenya to the French Republic, Portugal, Serbia, and Holy See in 2018. She served as Kenya’s highest-ranking representative, with direct responsibility for stewarding negotiations and delivering essential bi-lateral messages on behalf of Kenya. During the period 2013–2018, Professor Wakhungu served as Kenya’s Cabinet Secretary for Environment and Natural Resources, responsible for ensuring good governance in the protection, restoration, conservation, development, and management of the environment and natural resources. The technocrat was the Executive Director/Professor of the African Centre for Technology Studies (ACTS) in Nairobi from 2002 to 2013. She was at Pennsylvania State University, where she served as an associate professor of science, technology, and society and as director of the Women in Science and Engineering (WISE) Institute. Professor Wakhungu was the Technical Advisor to the Group Energy Management Assistance Programme, World Bank, from 2010 to 2013, and Research Director of the Global Energy Policy and Planning Programme of the Toronto-based International Federation of Institutes for Advanced Study (IFIAS), Project Leader of the Renewable Energy Technology Dissemination Project of the Stockholm Environment Institute (SEI). She has had the distinction of being the “designated energy expert” for the United Nations Commission of Science and Technology for Development (Gender Working Group). Professor Wakhungu received a BS in Geology from St. Lawrence University, New York, an M.S. degree in Petroleum Geology from Acadia University, Canada, and a PhD in Energy Resources Management from Pennsylvania State University. She was awarded an honorary doctorate from the University of Reading in 2017. She is a member of the Giants Club, which brings visionary leaders together to support the protection of elephants. She is the recipient of several honours and awards, including the Clark R. Bavin Wildlife Law Enforcement Award, 2016.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".