South African research in the Southern Ocean : new opportunities but serious challenges : : commentary
Bibliographic record
Abstract
South Africa has a long track record in Southern Ocean and Antarctic research and has recently invested considerable funds in acquiring new infrastructure for ongoing support of this research. This infrastructure includes a new base at Marion Island and a purpose-built ice capable research vessel, which greatly expand research opportunities. Despite this investment, South Africa's standing as a participant in this critical field is threatened by confusion, lack of funding, lack of consultation and lack of transparency. The research endeavour is presently bedevilled by political manoeuvring among groups with divergent interests that too often have little to do with science, while past and present contributors of research are excluded from discussions that aim to formulate research strategy. This state of affairs is detrimental to the country's aims of developing a leadership role in climate change and Antarctic research and squanders both financial and human capital.
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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 | 0.038 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.045 | 0.038 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".