The Public and Professionals Reason Similarly about the Management of Non-Native Invasive Species: A Quantitative Investigation of the Relationship between Beliefs and Attitudes
Bibliographic record
Abstract
(Uploaded by Plazi for the IPBES Invasive Alien Species Assessment) Despite continued critique of the idea of clear boundaries between scientific and lay knowledge, the 'deficit-model' of public understanding of ecological issues still seems prevalent in discourses of biodiversity management. Prominent invasion biologists, for example, still argue that citizens need to be educated so that they accept scientists' views on the management of non-native invasive species. We conducted a questionnaire-based survey with members of the public and professionals in invasive species management (n = 732) in Canada and the UK to investigate commonalities and differences in their perceptions of species and, more importantly, how these perceptions were connected to attitudes towards species management. Both native and non-native mammal and tree species were included. Professionals tended to have more extreme views than the public, especially in relation to nativeness and abundance of a species. In both groups, species that were perceived to be more abundant, non-native, unattractive or harmful to nature and the economy were more likely to be regarded as in need of management. While perceptions of species and attitudes towards management thus often differed between public and professionals, these perceptions were linked to attitudes in very similar ways across the two groups. This suggests that ways of reasoning about invasive species employed by professionals and the public might be more compatible with each other than commonly thought. We recommend that managers and local people engage in open discussion about each other's beliefs and attitudes prior to an invasive species control programme. This could ultimately reduce conflict over invasive species control.
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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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".