Policy-Oriented Research in Invasion Science: Trends, Status, Gaps, and Lessons
Bibliographic record
Abstract
Abstract Invasive alien species are a major driver of global environmental change. Escalating globalization processes such as international trade and long-distance transport have contributed to an increase in the ecological, economic, and sociocultural impacts of biological invasions. As a result, their management has become an increasingly relevant topic on environmental policy agendas. To better understand the role of policy in invasion science and to identify trends and gaps in policy-oriented research, a systematic literature review was conducted covering 2135 publications. The results highlight that international policy instruments are contributing to an increased interest in pursuing policy-oriented research. Specifically, key historical periods in policy development (e.g., the Convention on Biological Diversity’s COP10 in 2010) coincide with periods of active policy-focused research in invasion science. Research is, however, more applied to local scales (i.e., subnational, and national) and is more focused in places with high research capacity or where severe environmental or economic impacts are well documented.
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 | 0.085 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.031 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".