Bibliographic record
Abstract
The search for answers to the issue of global sustainability has become increasingly urgent. In the context of higher education, many universities and academics are seeking new insights that can shift our dependence on ways of living that rely on the exploitation of so many and the degradation of so much of our planet. This is the vision that drives SANORD and many of the researchers and institutions within its network. Although much of the research is on a relatively small scale, the vision is steadily gaining momentum, forging dynamic collaborations and pathways to new knowledge.The contributors to this book cover a variety of subject areas and offer fresh insights about chronically under-researched parts of the world. Others document and critically reflect on innovative approaches to cross-continental teaching and research collaborations. This book will be of interest to anyone involved in the transformation of higher education or the practicalities of cross-continental and cross-disciplinary academic collaboration. The Southern African-Nordic Centre (SANORD) is a network of higher education institutions from Denmark, Finland, Iceland, Norway, Sweden, Botswana, Namibia, Malawi, South Africa, Zambia and Zimbabwe. Universities in the southern African and Nordic regions that are not yet members are encouraged to join.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.046 | 0.024 |
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".