Where and how can Africa and India leverage the blue economy opportunities of the Indian Ocean region as a driver for sustainable development and partnerships?
Notice bibliographique
Résumé
Through the blue economy (BE), Africa and India can attain sustainable development, transnational partnerships, and continental engagement targets, never been seen before. However, efforts on how this could be done have been pedestrian and less explored. This review and perspective paper utilizes a bibliometric analysis technique to analyze 1712 documents, systematically sourced from Scopus. Thus, this paper situates itself as one of the first scholarly pieces to comprehensively highlight strategic aspects that could advance sustainable Africa-India regional development partnership. Mixed comparative results are found in the literature. Since 2012, research on the BE in Africa and India has increased. The BE is emphasized as a critical topical issue in Africa, albeit this is mostly led by non-African scholars and institutions. In India, most BE research perspectives target regional issues, e.g., in the Indo-Pacific region. African researchers have published more in high-impact journals compared to their Indian counterparts. The annual growth rate of research on the BE in India is comparatively higher than that of Africa (8.69 to 5.49 percent, respectively). However, the average citations of research in all regions are declining. African authors have higher national and international co-authorship collaborations. Collaborations between Africa and India on the BE are few. Most country-level collaborations are with developed nations. Nevertheless, there is recognition of the increasing vulnerability of Africa's and India's coastal communities to megatrends and marine environmental threats. Most documents emphasize that the resource endowments in the Indian Ocean (IO) could mitigate maritime challenges to socioeconomic development and environmental stewardship. Five valuable findings are emphasized: (1) the BE is essential to the prospects of sustainable development, (2) inclusive and sustainable actions are needed to address coastal socioecological shifts, (3) several BE solutions are proposed but not put into practice, and (4) BE partnerships in the IO must include China and other emerging states of the Global South, and (5) the IO is paramount towards sustainable BE between Africa and India. Borrowing from the literature insights, and as a contribution to BE-led sustainable development partnerships between Africa and India, five strategic leverage points are identified and developed: socio-cultural, economic, institutional, environmental, and scientific. As the development of BE engagements and partnership is a new development arena in Africa and India, policymakers and researchers should: (a) initiate the Africa-India BE journal, b) leverage and link Africa's and India's existing BE initiatives, visions, and programs, c) reimagine Africa and India’s development connotations, d) start slowly but consistently, and e) recognize existing shared sustainability or sustainable development visions. To achieve this, the IO must be recognized as a shared natural resource that has the potential to compartmentalize and link the proposed leverage points. Thus, policymakers and researchers must work towards rejuvenating shared ties, histories, vulnerabilities, and BE visions. This can help strengthen regional partnerships, trust, and collaborations for a better and sustainable BE.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,005 | 0,012 |
| Études des sciences et des technologies | 0,003 | 0,005 |
| Communication savante | 0,025 | 0,015 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».