Bibliographic record
Abstract
One of the main underlying drivers of New Zealand’s knowledge economy, university science education, has become a victim of its own success. New Zealand science graduates are well trained in core analytical areas and they enjoy high income. Many pursue advanced degrees and they frequently have the freedom to pursue their strong interests in science. New Zealand’s university science schools have served their students well, educating them to world-class standards but those students are increasingly going overseas because of a lack of opportunity in New Zealand. Currently, about 20 % of recent university science graduates are working overseas, and this number may rise to 30%, or even 40%, in the next few years. To make matters worse, it is our most creative scientists that are either overseas, or packing their bags to go. These findings come out of a comprehensive study of over 1,400 recent science graduates from all eight New Zealand universities. Respondents were university science graduates who have graduated in the last ten years. The study was designed to focus on the role creativity plays in scientific advances. The two main components of what makes a creative scientist are love of science and the freedom to explore scientific ideas. Both these were common characteristics of those who responded to the survey. For most university science graduates the fact that they are well paid is a secondary issue. Most take on careers in science for love and not money. The availability of appropriate science jobs was, however more in question. Only about a quarter of science graduates do not work in science and this may be due to personal preferences. Many, New Zealand science jobs do not, however offer the freedom, challenge and other attractions
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.614 | 0.561 |
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; the direct Gemma label and the distilled Codex classifier 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".