Scale issues in marine ecosystems and human interactions
Bibliographic record
Abstract
Abstract Understanding the reciprocal interactions between humans and marine ecosystems has several fundamental difficulties, in particular compatible methodologies and different analytical scales. The issue of scale is central, as the scales chosen for studies of marine systems and human interactions can constrain recognition of the drivers and responses of these systems to global changes. The essential task is to discover how to combine social and natural science scale analyses to understand the impact of natural systems on people and the impact of people on natural systems. We identify characteristic spatial, temporal and organizational scales in marine ecosystems and human interactions, and the difficulties inherent in their cross‐disciplinary application. An approach is suggested focusing on communities of fish and fishers that makes explicit: (1) the need to manage marine resources in such a way as to encompass global to local scales; (2) recognition of the complementary nature of organizational scales between the natural and social sciences and use of appropriate natural science scales in the development of management policies; (3) the need to be aware of shifting temporal baselines and the representative nature of the data over time, for both social and natural sciences; and (4) caution regarding predictive models when humans are included. In terms of methodologies, good scale matches occur across large‐scale social and natural science models and surveys, but problems remain in small‐scale qualitative social studies and in cross‐scale studies. Cumulative case studies appear to provide the best approach, although ‘integrating up’ remains a challenge. Natural and social scientists need to work together to identify these issues of ecosystem processes and human interactions, and their appropriate scales.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".