Bibliographic record
Abstract
Leading invasion biologists sometimes dismiss critics and criticisms of their field by invoking "the straw man" fallacy. Critics of invasion biology are also labelled as a small group of "naysayers" or "contrarians", who are sometimes engaging in "science denialism". Such unfortunate labels can be seen as a way to possibly suppress legitimate debates and dismiss or minimize reasonable concerns about some aspects of invasion biology, including the uncertainties about the geographic origins and complex environmental impacts of species, and the control programs against species perceived as "invasive". In assessing the quality of the debate in this area, we examine the validity of the use of various strategies, including the "straw man" concept, and explore a range of potential logical fallacies present in some recent prominent discussions about invasion biology and so-called "invasive" species. The goal is to add some clarity to the concepts involved, point out some problematic issues, and improve the quality of the debates as the discussions move forward.
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 | 0.038 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.100 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".