Different coasts for different folks: Place-based community values and experience mediate social acceptability of low-trophic aquaculture
Bibliographic record
Abstract
The expansion of low-trophic aquaculture (shellfish and sea plants) is limited in many regions by a fragmented regulatory process that is difficult for smallholder farmers to navigate. Small-scale Aquaculture Development Areas (ADAs) can remove some of this regulatory burden by establishing pre-approved zones for aquaculture development; however, an understanding of local support for low-trophic aquaculture is needed to understand the potential of ADAs. A survey was used to solicit information about community support for shellfish and sea plant aquaculture in Pictou County, a coastal area of Nova Scotia, Canada. Participants had a positive impression of low-trophic aquaculture, but residents in one coastal area reported greater perceived negative impacts on the recreational use and enjoyment of coastal areas and views, while residents in another coastal area reported a higher level of support for shellfish aquaculture. In general, participants also valued community involvement in aquaculture management, local ownership of farms, and community benefits from the presence of farms. Results suggest that top-down communication is unlikely to play a significant role in acceptability. Instead, experience of low trophic aquaculture and place-based values are important for understanding social acceptability. Community involvement in the development of ADAs and the distribution of benefits from farming could support trust in ADAs and social licence for low-trophic aquaculture. • Acceptability and regulatory burden are barriers to low-trophic aquaculture (LTA). • Experience is more important than knowledge in acceptability of LTA. • Place-based values that underpin LTA acceptability differ at small spatial scales. • Procedural and distributional fairness and trust are important for LTA acceptability. • Aquaculture development areas can support development and social licence for LTA.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".