0- Editorial - Building the Vision: Higher Education and Quality Assurance in East Africa
Bibliographic record
Abstract
The East African Higher Education Quality Assurance ForumThe East African Higher Education Quality Assurance Network (EAQAN) is a network of quality assurance practitioners in the East African region.The Network was formally established in 2012 in Entebbe following the DIES (Dialogue on Innovative Education Strategies) initiative, a partnership between the IUCEA (Inter-University for East Africa), DAAD (German Academic Exchange Service) and higher education commissions in the region, to enhance quality of higher education in the East African region.The EAQAN was established primarily to provide a platform for discussion and exchange of experiences among quality assurance (QA) coordinators and other stakeholders in quality assurance, teaching and learning as well as related issues in the management of higher education.Following agreement during the EAQAN General Assemblies the major activity of the EAQAN has been to host capacity building and knowledge sharing QA forums in May every year since 2012.The forums have been funded by the IUCEA and DAAD with expertise provided by the HRK (The German Rectors' Conference) and other higher education institutions in the region.What follows in this edition is a compilation of a selection of key papers from the 2015 forum, held in Nairobi, Kenya, where over eighty universities from Kenya, Tanzania, Uganda, Burundi and Rwanda participated, including the regulatory Higher Education Commissions of these countries.However, bringing together some of the most progressive thinkers in a single edition is both a challenge and an opportunity when one is addressing two areas of significance.Both 'higher education' and 'quality assurance' are
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.019 | 0.014 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".