Striving for Sustainability: The Contribution of Paul Johnston to Conservation Biology
Bibliographic record
Abstract
Paul Johnston, the lead scientist with Greenpeace International, combines scientific knowledge with public debate and awareness campaigns to work towards environmental change and sustainability. Opposed by numerous people internationally, Paul Johnston is in a constant battle to change negative public perceptions of Greenpeace and their scientific endeavors such as reviews and specific studies. Through his position with Greenpeace and as a credited biologist with a PhD in selenium toxicity in aquatic invertebrates he has been involved in numerous international conferences both with public organizations and industry. Paul Johnston has built up a reputation through his tireless efforts and, regardless of criticisms of actions or stances he may take, his dedication to his beliefs and beyond that the fact that he backs his claims with real world action demands respect in the fight against environmental degradation. There are few people who have not heard of Greenpeace and Paul Johnston's contributions in raising public awareness of environmental issues is important should society have a chance of changing.
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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".