Working for the environment: farmer attitudes towards sustainable farming actions in rural Wales, UK
Bibliographic record
Abstract
Recognition of land management impacts on water quality and flooding, and climate change-induced increases in storm intensity and flood risk, have led to interest in farmer provision of ecosystem services alongside food production. However, pathways for practical design and funding of agroecological interventions are less well understood. Effective design and implementation of sustainable farming initiatives have been linked to human-centred aspects including stakeholder engagement and provision of social and economic co-benefits. To obtain information on Welsh farmer perspectives on sustainable farming actions and aid development of agroecological policy and design guidance, Welsh farmer perspectives on sustainable farming were obtained through discussion, online polls, and questionnaires. Participant-identified barriers to action included incorporation of return on initial time and cost investment in long-term farm budgets, occurrence of extreme weather events, and tenanted land. Decision-making processes were rooted in community discussion to balance perceived needs of the land and farm business, with communication preferences expressed for bilingual farm advice provision and support of farmer-to-farmer knowledge transfer pathways. In addition to responding to research questions, participants identified interdependent components of economic, social, cultural, and environmental sustainability necessary to achieve positive environmental outcomes, and expressed environmentally oriented farming identities linked to environmental guardianship and caretaking. Design of tree-planting schemes was discussed as an example of this interlinkage, with positive attitudes expressed for land sharing at small spatial scales, but not at the whole-farm scale.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".