Marine social-ecological responses to environmental change and the impacts of globalization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Marine social–ecological systems consist of interactive ecological and human social elements so that changes in ecological systems affect fishing-dependent societies and vice versa. This study compares the responses of marine ecological and fishing-dependent systems to environmental change and the impacts of globalization, using four case-studies: NE Atlantic (Barents Sea), NW Atlantic (Newfoundland), SE Atlantic (Namibia) and the equatorial Atlantic (Ghana). Marine ecological systems cope with short-time changes by altering migration and distribution patterns, changing species composition, and changing diets and growth rates; over the longer term, adaptive changes lead to increased turn-over rates and changes in the structure and function of the system. Fishing communities cope with short-term change through intensification and diversification of fishing, migration and ‘riding out the storm’. Over the longer term, adaptive changes in policy and fisheries governance can interact with social–ecological change to focus on new fisheries, economic diversification, re-training, out-migration and community closures. Marine social–ecological systems can ultimately possess rapid adaptive capacity in their ecological components, but reduced adaptive capacity in society. Maintaining the diversity of response capabilities on short and longer time scales, among both ecological and human fishing systems, should be a key policy objective. The challenge is to develop robust governance approaches for coupled marine social–ecological systems that can respond to short- and long-term consequences of global change.
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.
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) | 0.001 | 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 it