Access, Rights and Equity for Blue Tenure Transitions in Small-Scale Fisheries
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,014 |
| Communication savante | 0,007 | 0,010 |
| Science ouverte | 0,001 | 0,009 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».