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As rural nonfarm activities grow in developing countries, less attention is being paid to the opportunities they may provide for women. The purpose of this study is to examine the gender-differentiated impact of nonfarm diversification strategies in rural Senegal.

This study uses data collected from the Senegalese poverty monitoring survey and employs an instrumental variable (IV) approach and a multinomial endogenous treatment model to investigate the extent to which diversification strategies lead to improved outcomes for rural women and their households.

While nonfarm diversification is a male-dominated livelihood strategy, rural women make the most of it, regardless of whether they diversify into low- or high-return nonfarm activities. At the individual level, diversification improves rural women’s well-being through large income-increasing effects and higher empowerment but has no effect on rural men’s well-being. At the household level, the authors find that, when only women diversify, households have lower per capita income but are less likely to be food insecure than when only men or both genders diversify.

This study is based on cross-sectional data, making it impossible to examine the dynamic effects of nonfarm diversification strategies on well-being outcomes.

This study contributes to the current literature on rural livelihood diversification. While much attention has been paid to the feminization of agriculture, remarkably little is known about the expanding role of rural women in the nonfarm sector.

As public health professionals strive to promote vaccines for inoculation efforts, fervent anti-vaccination movements are marshaling against it. This study is motived by a need to better understand the online discussion around vaccination. The authors identified the sentiments, emotions and topics of pro- and anti-vaxxers’ tweets, investigated their change since the pandemic started and further examined the associations between these content features and audiences’ engagement.

Utilizing a snowball sampling method, data were collected from the Twitter accounts of 100 pro-vaxxers (266,680 tweets) and 100 anti-vaxxers (248,425 tweets). The authors are adopting a zero-shot machine learning algorithm with a pre-trained transformer-based model for sentiment analysis and structural topic modeling to extract the topics. And the authors use the hurdle negative binomial model to test the relationships among sentiment/emotion, topics and engagement.

In general, pro-vaxxers used more positive tones and more emotions of joy in their tweets, while anti-vaxxers utilized more negative terms. The cues of sadness predominantly encourage retweets across the pro- and anti-vaccine corpus, while tweets amplifying the emotion of surprise are more attention-grabbing and getting more likes. Topic modeling of tweets yields the top 15 topics for pro- and anti-vaxxers separately. Among the pro-vaxxers’ tweets, the topics of “Child protection” and “COVID-19 situation” are positively predicting audiences’ engagement. For anti-vaxxers, the topics of “Supporting Trump,” “Injured children,” “COVID-19 situation,” “Media propaganda” and “Community building” are more appealing to audiences.

This study utilizes social media data and a state-of-art machine learning algorithm to generate insights into the development of emotionally appealing content and effective vaccine promotion strategies while combating coronavirus disease 2019 and moving toward a global recovery.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-03-2022-0186

Different technologies may currently be used to produce dental prostheses, such as additive manufacturing and traditional milling. This study aims to evaluate and improve the fabrication process for hot-pressed porcelain dental prostheses and compare the use of masked stereolithography apparatus (MSLA) casting to computer-aided design/computer-aided manufacturing (CAD/CAM) casting. The cost-benefit analysis of producing dental prostheses through various technologies, including additive manufacturing and traditional milling, has not been fully explored. The cost of materials and processes used to produce prostheses varies based on complexity of design and materials used, and long-term effects, such as durability and wear and tear, must be taken into account.

Using key elements of part costs and estimation cost models, a multivariable approach was used to evaluate the practicality of the recommended strategy and process improvement.

The research found that MSLA casting provides a higher return on investment than CAD/CAM casting, and the optimized production process could be more suitable for the size and annual demand for prostheses.

Overall, this study highlights the need for a more comprehensive understanding of the cost-benefit analysis of different dental prosthesis production methods and emphasises the importance of evaluating long-term effects on the cost-benefit analysis.