Bangladesh positioned as third rice producing country in the world. In Bangladesh, regional growth and trend in rice production determinants, disparities and similarities of rice production environments are highly desirable. In this study, the secondary time series data of area, production, and yield of rice from 1969–70 to 2019–20 were used to investigate the growth and trend by periodic, regional, seasonal and total basis. Quality checking, trend fitting, and classification analysis were performed by the Durbin-Watson test, Exponential growth model, Cochrane-Orcutt iteration method and clustering method. The production contribution to the national rice production of Boro rice is increasing at 0.97% per year, where Aus and Aman season production contribution significantly decreased by 0.48% and 0.49% per year. Among the regions, Mymensingh, Rangpur, Bogura, Jashore, Rajshahi, and Chattogram contributed the most i.e., 13.9%, 9.8%, 8.6%, 8.6%, 8.2%, and 8.0%, respectively. Nationally, the area of Aus and Aman had a decreasing trend with a -3.63% and -0.16% per year, respectively. But, in the recent period (Period III) increasing trend was observed in the most regions. The Boro cultivation area is increasing with a rate of 3.57% per year during 1984–85 to 2019–20. High yielding variety adoption rate has increased over the period and in recent years it has found 72% for Aus, 73.5% for Aman, and 98.4% for Boro season. As a result, the yield of the Aus, Aman, and Boro seasons has been found increasing growth for most of the regions. We have identified different cluster regions in different seasons, indicating high dissimilarities among the rice production regions in Bangladesh. The region-wise actionable plan should be taken to rapidly adopt new varieties, management technologies and extension activities in lower contributor regions to improve productivity. Cluster-wise, policy strategies should be implemented for top and less contributor regions to ensure rice security of Bangladesh.

Built on deep-rooted political and cultural heritage, ‘rice security’ is the foundation of ‘food security’ in Bangladesh. The country has been in production-surplus of rice in the current decade feeding over 165 million people. This on-going ‘selfsufficiency momentum’ would require to maintain to meet increased demand from growing future population. On developmental side, Bangladesh is placed among the three of the world’s fastest growing economies in the years through to 2050. Rice sector would need to match with the pace of this growth. In addition, agriculture sector, that includes rice, is to double the productivity as the government commits to meet the SDG goal 2.3.1. This study addresses those issues through scoping increased rice production and productivity in Bangladesh, developing a plan of work (POW) on translating the scope and designing implementation plans and actions, incorporating efficiency, resilience, stability and sustainability issues, to achieve the POW. The study has used brainstorming, and rigorous analysis to achieve the objectives. The productivity has been explained in terms of yield- and labour-productivity. The developed three-winged ‘doubling rice productivity (DRP)’ framework directs yield enhancement and production accumulation in unexplored spaces (Wing-1); increased adoption of mechanization to impact on labour productivity (Wing-2), and improvements in nutritional quality and rice-based product diversity, and stabilizing the farmgate price (Wing-3). Analyses show, from the baseline figure of 35.29 MT in 2015, rice production in the country can be raised to 46.90 MT in 2030, 54.09 MT in 2040 and 60.85 MT in 2050 with combined contributions of three pillars – yield improvements by enhanced varietal potential (Pillar 1), reduction in existing yield gap (Pillar 2) and production increase by exploring unexplored spaces for rice (Pillar 3) of Wing-1 of the DRP. This production will produce a surplus of 6.50, 10.29 and 13.65 MT in 2030, 2040 and 2050, respectively, over the production target (40.40, 43.80 and 47.20 MT in 2030 and 2050, respectively). Results further reveal that through scale-appropriate mechanization backed up by estimated fair price, labour productivity in rice will be doubled by 2029, meeting the SDG 2.3.1. Good number of released varieties have been identified to have specific nutritional trait, and value adding quality. We have emphasized on much needed actions on demand-driven research for varietal development and field-adoptable management, mechanization for transplanting and harvesting operations, accommodation of rice in unexplored spaces, farmer-based speedy seed multiplication and dissemination system, establishment of commission for agricultural costs and prices, input buffer stock terminals for managing production risk, long-term storage and export of surplus production, and research-publicity-market development for rice-based products through public-private partnership. It is concluded that efficiency, resilience and sustainability around the three wings of DRP in the rice production systems to be ensured to achieve the rice production, productivity and labour use estimates. Bangladesh Rice J. 24 (2): 1-47, 2021

Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981–2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). Out of 24 ML algorithms, the four best ML methods, ranger, bagEarth, support vector machine, and random forest (RF) have been identified for the prediction of multi-scale drought indices. The RF classifier and the Boruta algorithms shows that water balance, precipitation, maximum and minimum temperature have a higher influence on drought intensity and occurrence across Bangladesh. The trend of spatio-temporal analysis indicates, drought intensity has decreased over time, but return time has increased. There was significant variation in changing the spatial nature of drought intensity. Spatially, the drought intensity shifted from the northern to central and southern zones of Bangladesh, which had an adverse impact on crop production and the livelihood of rural and urban households. So, this precise study has important implications for the understanding of drought prediction and how to best mitigate its impacts. Additionally, the study emphasizes the need for better collaboration between relevant stakeholders, such as policymakers, researchers, communities, and local actors, to develop effective adaptation strategies and increase monitoring of weather conditions for the meticulous management of droughts in Bangladesh.

The gig economy (temporary, contract, and freelance online jobs rather than permanent positions) is a component of the fourth industrial revolution and preview of future work. The rise of digital platforms has increased career opportunities and income potential, particularly for women. Yet, the sex-disaggregated evidence regarding platform usage, employment characteristics, and working motivations and satisfaction remains untapped. Using data from a quantitative survey of Bangladeshi gig workers (242 men and 201 women) conducted in 2022, this paper addresses these gaps between male and female workers. The gig economy appears to be gender-segregated across digital platform usages and working categories. Women tend to prioritize digital work options for managing multiple responsibilities, while men are often driven by the potential for higher income. This study conceptually utilized the two-factor theory and empirically ordered a probit model to identify gender differences in job satisfaction. Job satisfaction was significantly increased by work-life balance, monthly income, and social-media connection, while an increase in working hours, complexity in payment systems, and unstable networks all led to a decrease in job satisfaction. The findings have implications for the future growth of the gig economy, provide new insights into gender differences in job satisfaction, and underscore the need for gender-sensitive policies in the online labor market.