The pesky problem of defining a ‘pest’: testing the pest management attitudes scale in the United Kingdom
Bibliographic record
Abstract
The Pest Management Attitudes (PMA) scale was developed to provide a unidimensional and versatile tool to assess attitudes toward introduced pests and their management. While the PMA has been tested and shown strong psychometric properties in samples from Aotearoa, New Zealand (NZ), it is only beginning to be used internationally. This study tested the utility and influence of wording of the PMA scale in the United Kingdom (UK), using a 2021 survey (N = 999) distributed via online platform Prolific. Two of the 9 PMA scale items were not appropriate in our UK sample. We posit that despite references to introduced and native species in the PMA wording, many participants completed the survey with human rather than biodiversity pests in mind. While the PMA remains a valuable tool for understanding attitudes toward pests and their management, wording may need modification to ensure that concepts translate cross-culturally to retain meaningful comparisons.
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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 | 0.022 | 0.099 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".