Access, Rights and Equity for Blue Tenure Transitions in Small-Scale Fisheries
Bibliographic record
Abstract
Globally, small-scale fisheries (SSF) support over 94% of the 120 million people engaged in capture fisheries. An estimated 5.8 million fishers in the world earn less than $1 per day, yet they generate an estimated two-thirds of the global fish catch for direct human consumption, with fish being a key source of local food security. According to the Voluntary Guidelines on the Responsible Governance of Tenure of Land, Fisheries and Forests in the Context of National Food Security, (2012), tenure systems are defined as the rules and norms that determine who can access what resources and their spatial and temporal attributes. The FAO’s Voluntary Guidelines for Securing Sustainable Small-Scale Fisheries (2015) identify the governance of tenure as a fundamental requirement for responsible and sustainable use of aquatic biodiversity and natural resources.In the Western Indian Ocean (WIO) region, the importance of small-scale fishers to broader sustainability outcomes is crucial. In the WIO region, small-scale fishers are strongly anchored in local communities, reflect a way of life, and provide critical contributions to society, economy, culture, and environment. At the same time, there has been a rapid increase in regional dialogues and actions related to WIO blue economy initiatives and global conservation targets catalyzed by multi-lateral agencies, global development and conservation organizations and regional governments. At the core of these initiatives are substantive challenges and/or threats to marine tenure of SSF and coastal communities generally. In our presentation, we highlight in particular two specific gaps which the Blue Tenure Transitions (BTT) working group is addressing. First, how we are building the transdisciplinary science base for the WIO region on the specific impacts and implications of marine tenure and the social, culture, economic, and ecological challenges of inadequate tenure provisions in the context of Blue Economy and 30x30 initiatives such as Marine Spatial Planning in countries such as South Africa and Tanzania. Second, we will present how we are co-developing participatory methodologies that enable communities to map and subsequently ‘share their stories’ about marine tenure in creative and accessible ways (through visuals and artforms and/or narratives) that empower them to advocate for necessary reforms. Our overall objective is to support community tenure systems and highlight bright spots where tenure has led to positive social and ecological benefits to ensure small-scale fisheries have equitable access to ocean resources, and help co-generate policies and practices that help protect and enable small-scale fishers. Working group members in the BTT project are funded by the Western Indian Ocean Marine Science Association and are based in both academic and government positions, from the University of Cape Town, South Africa, Institute for Coastal and Marine Research at the Nelson Mandela University, South Africa, Rhodes University, South Africa, Institute of Marine Science at the University of Dar es Salaam, Tanzania, Ministry of Fisheries and Blue Economy, Zanzibar, South African Department of Forestry, Fisheries and the Environment, South African National Biodiversity Institute, and the Vulnerability to Viability Global Partnership for Small-Scale Fisheries at the University of Waterloo in Canada.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.001 |
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".