Altered ontologies of the seascape: local knowledge, environmental change and conservation in Kihnu, Estonia
Bibliographic record
Abstract
This article explores the roots and paths of changing discourses about the natural environment and marine resources in the seascape of Kihnu, Estonia. The ontology of the seascape is never static, being subjected to constant transformation, as local experiences and understandings collide with external influences, regulations and constraints. By focusing on the indeterminacies of agency, and human encounters and environmental events, I show how Soviet pasts and perceptions, shifting scientific paradigms and practices, the dynamics of local-global articulations, and unforeseen transformation in the marine environment have progressively contributed to new understandings of the seascape, seals and other marine resources. These changing perceptions fundamentally challenge previously-held notions that humans and nature belong together. A traditional seal hunt had endured in the Baltic Sea for centuries, but the decline of the seal population in the 1970s was widely understood as anthropogenic, related to overfishing, large scale seal hunts and pollution. While most Baltic Sea coastal waters have remained closed to any type of seal hunting for more than 40 years, many fishers and marine scientists agree that grey seal population has recovered and some Baltic Sea countries have lifted the ban on hunting grey seal. While the seal hunt and meat used to have great cultural importance, there was also commercial value in seal skin and fat for many coastal communities. Several representatives of fishery-dependent coastal communities in Estonia now publicly express a view that seals now compete with fishers. Consequently the seal has lost its cultural importance and is considered as an intruder to Kihnu cultural space. I argue that making sense of the concerns and uncertainties that presently surround the question of knowing about and managing marine ecosystems, requires paying close attention to the ways in which access to the seascape and its resources have been enforced and altered over time.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".