Women's Vulnerabilities in Natural Disasters: A Study in Coastal Bangladesh

Amran Hossain, Ayesha Sultana — Tue, 14 Oct 2025 00:00:00 -0500

Purpose: Bangladesh is widely acknowledged as one of the most disaster-prone countries in the world. In the coastal zone, women are more vulnerable to natural disasters. The study aims to explore the multifaceted vulnerabilities faced by women during and after natural disasters in the coastal area of Bangladesh.

Design/methodology/approach: A mixed approach was employed in this study, where primary data were collected for the survey from a total of 150 respondents via face-to-face interviews based on purposive sampling. Moreover, 10 in-depth interviews were conducted using semi-structured interview schedules to gain a deeper understanding of the phenomena under study.

Findings: The study found that women face numerous challenges during and after disasters, including inadequate shelter facilities, insufficient sanitation, lack of privacy, sexual harassment, health risks, and barriers to menstrual hygiene management. The study also found that pregnant women faced severe hardships in accessing healthcare. Additionally, disasters contribute to increased school dropouts, early marriages, domestic violence, psychological distress, and economic insecurity.

Conclusion: The study suggests that gender-sensitive disaster management policies are urgently required to address these vulnerabilities and enhance women's resilience in disaster-prone coastal areas.

Artificial Intelligence and Foresight for a Decolonized Education Model in Niger

Maman Sillimana — Fri, 24 Oct 2025 00:00:00 -0500

This study explores how to integrate artificial intelligence in the Nigerien educational system, based on a systematic review of twenty-seven institutional and scientific documents published between 2018 and 2023. The methodology, inspired by Glaser and Strauss’ grounded theory, enabled a rigorous thematic analysis of reports from the Ministry of National Education, studies by the World Bank and UNESCO, and publications from national research centers such as LASDEL and Abdou Moumouni University of Niamey. Results indicate that artificial intelligence has significant potential to address three major structural challenges. It can reduce class overcrowding, where the national ratio is one teacher for fifty-six students, overcome language barriers in a context where fewer than thirty percent of primary school entrants are proficient in French, the official language of instruction, and mitigate the chronic lack of educational resources. Pilot projects such as the “Smart Schools” demonstrated learning gains of fifteen to twenty-three percent. The study also identifies key obstacles, including low school connectivity, high dependence on imported educational content, and the absence of a locally adapted ethical framework. To overcome these challenges, a contextualized and decolonized integration model is proposed over three phases from 2024 to 2035. It prioritizes low-tech and energy-efficient solutions, the inclusion of national languages from the design stage, and strengthened teacher training and support. Priority applications include intelligent tutoring in local languages and the use of data analytics to optimize resource management, especially in marginalized rural areas. This research establishes theoretical and practical foundations for a renewed Nigerien educational model where artificial intelligence acts as a lever for pedagogical empowerment and technological sovereignty. By emphasizing contextualization, epistemic decolonization, and cultural grounding, the study contributes to the development of an ambitious and locally rooted African model of educational innovation.

Nurture

Women's Vulnerabilities in Natural Disasters: A Study in Coastal Bangladesh

Artificial Intelligence and Foresight for a Decolonized Education Model in Niger