case study from the southern Cape linefishery 2: Considering one’s options when the fish leave
Bibliographic record
Abstract
Fishers in the small-scale, commercial linefishery in the southern Cape, South Africa, are exposed to variability and change in the marine social-ecological system of which they are a part. Faced with multi-scalar changes within this complex system, fishers employ a wide range of strategies in reaction to change. As part of a broader study of stressors that bring about change in these systems, this contribution examines the fishers’ responses to these changes and is based on a participant-led, semi-structured interview process of skippers/boat owners, crew, processors and spouses/partners, in six communities in the southern Cape region, and has been supplemented with appropriate secondary data. The results are discussed using a resilience framework. The data were initially considered thematically by stressor, but results identified that a place-based analysis was equally important. Three major groupings were identified: (1) fishers who adapt and show clear business-orientation, (2) fishers who cope, and (3) fishers who react and are thus caught in a poverty trap. In addition to place-specific history, local feedback loops and indirect effects need to be better accounted for to understand these responses to change at various scales. The results of this study are expected to contribute to the basis of scenario planning in the region. Significance: Analysis of responses to change strategies provides insight into resilience displayed as well as costs and benefits of strategies. The description of strategies provides valuable insights into the decision-making processes in linefishery in the southern Cape. Cognitive and reflexive decision-making processes are shaped by individuals’ and communities’ experiences of past and present. Practical implications of actions are not always the overriding concern in decision-making, which underscores the importance and influence of culture. These results provide important insights into a system that is not well described, and highlight knowledge gaps that require further context-specific research.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".