The conservation “myths” we live by: Reimagining human–nature relationships within the Scottish marine policy context
Bibliographic record
Abstract
There are growing calls for the articulation and consideration of different value systems and emotions in shaping conservation and natural resource management decisions and participatory resource governance. This requires recognition of the socio‐cultural relations attached to landscape and seascape in marine conservation policy. Taking into account the relationship between the socio‐natural environment and socio‐political institutions and processes complicates conservation. Making human values and assumptions explicit within the conservation discourse reveals the inadequacy of conservation that is focused on a biodiversity that is framed only as other‐than‐human nature. This paper considers how the perceived separation between nature and culture underpinning conservation policy and practice exacerbated a conflict between members of a small Scottish island community and the Scottish Government around the creation of a marine protected area ( MPA ) off the coast of the island. A rich maritime heritage and a distinctive way of knowing the sea suggested the presence of embedded values that appeared to be colliding with values driving the MPA designation process. Social, historical and cultural forces have shaped the perceptions of landscape and seascape of many of the islanders and can help to explain the local resistance to the MPA . Visual participatory methods were used to explore local understandings of the meaning of conservation. The case‐study offers insights into different ways in which marine spaces are conceptualised and how this relates to marine resource governance. It contributes to a more complete understanding of human relations with the marine environment in the context of a marine conservation conflict.
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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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.083 |
| Scholarly communication | 0.024 | 0.021 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".