Undergraduate and graduate programmes in astronomy for the developing world
Bibliographic record
Abstract
Abstract In this paper, I discuss some aspects of the design of undergraduate and graduate astronomy curricula, broadly defined, for developing countries. A fundamental requirement is to develop students' ability and desire to learn, both in university and beyond. I then discuss several aspects of the curriculum: (i) The programme of coursework in astronomy and related topics such as physics and mathematics; (ii) The associated practical and project work to develop skills as well as knowledge; (iii) Linking the coursework, effectively, to various aspects of research; (iv) Development of general academic and professional skills such as oral and written communication, teaching, planning and management, and the ability to function as part of an interdisciplinary team; and (v) Orientation to the culture of the university and to the science and the profession of astronomy. To accomplish all of these goals may seem daunting, especially as many of them are not achieved in the most affluent universities. But much can be gained by recognizing that there are well-established “best practices” in education, achieved through formal education research, reflection, and experience. Simple resources, effectively used, can be superior to the highest technology, used without careful thought. It is often best to do a few things well; “less can be more”. And effective partnership, both within the local university and with the outside astronomical community, can also contribute to success.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".