•We study the impacts of women’s Self-help group membership on women’s and men’s empowerment.•We measure empowerment using two alternate indices: the A-WEAI and the Pro-WEAI.•We find that SHG ...membership has a significant positive impact on aggregate measures of women’s empowerment.•We also find that SHG membership reduces the gap between men’s and women’s empowerment scores.•The impacts are driven by increase in control over income, decisionmaking over credit, and active involvement in groups.
Women’s groups are important rural social and financial institutions in South Asia. In India, a large majority of women’s groups programs are implemented through self-help groups (SHGs). Originally designed as savings and credit groups, the role of SHGs has expanded to include creating health and nutrition awareness, improving governance, and addressing social issues related to gender- and caste-based discrimination. This paper uses panel data from 1470 rural Indian women from five states to study the impact of SHG membership on women’s empowerment in agriculture, using the project-level Women’s Empowerment in Agriculture Index (pro-WEAI) and the abbreviated Women’s Empowerment in Agriculture Index (A-WEAI). Because SHG membership was not randomized and women who self-select to be SHG members may be systematically different from non-members, we employ nearest neighbor matching methods to attribute the impact of SHG membership on women’s empowerment in agriculture and intrahousehold inequality.
Our findings suggest that SHG membership has a significant positive impact on aggregate measures of women’s empowerment and reduces the gap between men’s and women’s empowerment scores. This improvement in aggregate empowerment is driven by improvements in women’s scores, not a deterioration in men’s. Greater control over income, greater decisionmaking over credit, and (somewhat mechanistically, given the treatment) greater and more active involvement in groups within the community lead to improvements in women’s scores. However, impacts on other areas of empowerment are limited. The insignificant impacts on attitudes towards domestic violence and respect within the household suggest that women’s groups alone may be insufficient to change deep-seated gender norms that disempower women. Our results have implications for the design and scale-up of women’s group-based programs in South Asia, including the possibility that involving men is needed to change gender norms.
•Our paper explores the link between women's self-help groups and public entitlements.•It further examines the effect of SHG membership on social networks and mobility.•Empirical strategy employs ...matching methods to correct endogeneity of SHG membership.•Using data from rural India, we find that SHG members are more politically engaged.•SHG members are more likely to know of certain public entitlements than non-members.•SHG members are also more likely to avail of these public entitlement schemes.•SHG members also have wider social networks and greater mobility than non-members.
Women’s self-help groups (SHGs) have increasingly been used as a vehicle for social, political, and economic empowerment as well as a platform for service delivery. Although a growing body of literature shows evidence of positive impacts of SHGs on various measures of empowerment, our understanding of ways in which SHGs improve awareness and use of public services is limited. To fill this knowledge gap, this paper first examines how SHG membership is associated with political participation, awareness, and use of government entitlement schemes. It further examines the effect of SHG membership on various measures of social networks and mobility. Using data collected in 2015 across five Indian states and matching methods to correct for endogeneity of SHG membership, we find that SHG members are more politically engaged. We also find that SHG members are not only more likely to know of certain public entitlements than non-members, they are significantly more likely to avail of a greater number of public entitlement schemes. Additionally, SHG members have wider social networks and greater mobility as compared to non-members. Our results suggest that SHGs have the potential to increase their members’ ability to hold public entities accountable and demand what is rightfully theirs. An important insight, however, is that the SHGs themselves cannot be expected to increase knowledge of public entitlement schemes in absence of a deliberate effort to do so by an external agency.
Inclusive agricultural growth is important for overall economic growth and particularly critical for rural socio-economic stability and poverty reduction in Pakistan. The majority of Pakistan's ...population and 44 percent of the overall labour force are dependent upon agriculture which only accounts for a little over 20 percent of national GDP. The paper highlights some basic constraints that have not been explicitly addressed in the policy research and implementation and have impeded inclusive agriculture growth. A descriptive analysis based on data from the Agriculture Census of Pakistan and the Pakistan Household Income and Economic Survey—both of which were conducted in 2010-11—is used to show how high levels of poverty and its disparity across regions, combined with the declining size of operated holdings and associated fragmentation especially in the smallest size categories which now form over 60 percent of the agricultural holdings in Pakistan, are fundamental constraints. Poverty is both the result as well as the consequence of fragmented markets, weak institutions including governance; and, inadequate policy research and implementation. A better research based policy understanding of some basic constraints, and the variations across regions in such factors such as the declining size and fragmentation of operated farms, rural poverty; and, the levels of market development and institutions is essential along with effective implementation. One size fits all policies have not and will not work.
Interaction within mothers’ social networks can theoretically diffuse messages from interventions and campaigns into norms and practices for infant and young child feeding (IYCF).
We hypothesized ...that mothers’ social networks, diffusion of information, and social norms differed in intensive intensive interpersonal counseling (IPC), community mobilization (CM), and mass media (MM) compared with nonintensive (standard IPC and less-intensive CM and MM) intervention areas, were associated with IYCF practices, and partly explained practice improvement.
We conducted household surveys at endline in 2014 and follow-up in 2016 (n = ∼2000 each round). We used multiple regression to test differences and changes in networks, diffusion, and norms within intervention areas. We analyzed paths from intervention exposure to IYCF practices through networks, diffusion, and norms.
Mothers’ networks were larger in intensive than in nonintensive areas in 2014 and increased in both areas over time 25–38 percentage points (pp). The prevalence of receipt of IYCF information was high, with no changes over time in intensive areas but an increase in nonintensive areas (8–16 pp). In both areas, more family members and health workers provided IYCF information over time. Sharing of information increased 17–23 pp in intensive and 11–41 pp in nonintensive areas over time. Perceived descriptive norms improved 8–16 pp in intensive and 17–28 pp in nonintensive areas. Perceived injunctive norms were high in both areas. Breastfeeding practices were associated with networks, diffusion, and norms (OR: 1.6–4.4 times larger comparing highest with lowest quartile). Minimum dietary diversity was associated with larger networks and diffusion (OR: 1.5–2.2) but not with social norms. Indirect paths from intervention exposure to practices explained 34–78% of total effects.
Diffusion of IYCF information through social networks, reinforced by positive social norms for messages promoted over time, will contribute to positive changes in IYCF practices that may be achieved and sustained through large-scale social and behavior change interventions. This trial was registered at clinicaltrials.gov as NCT0274084.
This paper evaluates whether politician identity, and in particular, the party affiliation of legislators affects employment and welfare outcomes for minorities in India. I combine data on the ...outcome of close elections to state legislative assemblies over 18 years for 19 Indian states with data on employment and access to social security benefits to determine whether an increase in political representation by legislators belonging to India’s right-wing, Hindu nationalist party, the Bharatiya Janata Party (BJP), has a meaningful and causal effect on Muslim development outcomes. Close elections provide a unique window of opportunity to capture random variation in the assignment of legislators to certain districts in India. This natural experiment allows me to isolate the effect of a random increase in BJP political representation using the share of seats won by the BJP in close elections as an instrument for the share of seats won by the BJP across all elections. I find that increasing the district-level proportion of BJP legislators when the BJP is in power at the state-level reduces the likelihood of Muslim employment in both the public and private sector as well as the probability of Muslims having access to social security benefits. These results remain robust with the addition of various individual-level and electoral controls as well as with variations in the definition of a close election. I find no evidence of an adverse effect on Muslims with an increase in the political representation of the Indian National Congress (INC).
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•C. Sinensis leaf extract was undergone for Ni nanoparticle synthesis.•Particles were characterized by SEM, EDX and XRD and VSM techniques.•The NPs size was in the range of ...43.87–48.76nm.•NiNPs shows promising photo-catalytic activity.
Recently, the biosynthesis of nanoparticle attracted the attention of scientific community due to its simplicity, ease and eco-friendly nature. In the present study, Camellia Sinensis (C. Sinensis) leaves extract was employed for the synthesis of nickel nanoparticles (NiNPs). The fabricated NiNPs were characterized by scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX) and X-ray diffraction techniques. The photocatalytic activity (PCA) was evaluated by degrading crystal violet (CV) dye. The NiNPs size was in the range of 43.87–48.76nm, spherical in shape and uniformly distributed with magnetization saturation of 0.073 emu/g. The NiNPs showed promising PCA under solar light irradiation. At optimized conditions, up to 99.5% CV dye degradation was achieved. Results revealed that biosynthesis can be adopted for the synthesis of NiNPs in nano-size range since it is simple, cost effective and eco-friendly in nature versus physico-chemical methods.
Skin cancer represents one of the most lethal and prevalent types of cancer observed in the human population. When diagnosed in its early stages, melanoma, a form of skin cancer, can be effectively ...treated and cured. Machine learning algorithms play a crucial role in facilitating the timely detection of skin cancer and aiding in the accurate diagnosis and appropriate treatment of patients. However, the implementation of traditional machine learning approaches for skin disease diagnosis is impeded by privacy regulations, which necessitate centralized processing of patient data in cloud environments. To overcome the challenges associated with data privacy, federated learning emerges as a promising solution, enabling the development of privacy-aware healthcare systems for skin cancer diagnosis. This paper presents a comprehensive review that examines the obstacles faced by conventional machine learning algorithms and explores the integration of federated learning in the context of privacy-conscious skin cancer prediction healthcare systems. It provides discussion on the various datasets available for skin cancer prediction and provides a performance comparison of various machine learning and federated learning techniques for skin lesion prediction. The objective is to highlight the advantages offered by federated learning and its potential for addressing privacy concerns in the realm of skin cancer diagnosis.
The accurate and timely diagnosis of skin cancer is crucial as it can be a life-threatening disease. However, the implementation of traditional machine learning algorithms in healthcare settings is ...faced with significant challenges due to data privacy concerns. To tackle this issue, we propose a privacy-aware machine learning approach for skin cancer detection that utilizes asynchronous federated learning and convolutional neural networks (CNNs). Our method optimizes communication rounds by dividing the CNN layers into shallow and deep layers, with the shallow layers being updated more frequently. In order to enhance the accuracy and convergence of the central model, we introduce a temporally weighted aggregation approach that takes advantage of previously trained local models. Our approach is evaluated on a skin cancer dataset, and the results show that it outperforms existing methods in terms of accuracy and communication cost. Specifically, our approach achieves a higher accuracy rate while requiring fewer communication rounds. The results suggest that our proposed method can be a promising solution for improving skin cancer diagnosis while also addressing data privacy concerns in healthcare settings.
Healthcare professionals consider predicting heart disease an essential task and deep learning has proven to be a promising approach for achieving this goal. This research paper introduces a novel ...method called the asynchronous federated deep learning approach for cardiac prediction (AFLCP), which combines a heart disease dataset and deep neural networks (DNNs) with an asynchronous learning technique. The proposed approach employs a method for asynchronously updating the parameters of DNNs and incorporates a temporally weighted aggregation technique to enhance the accuracy and convergence of the central model. To evaluate the effectiveness of the proposed AFLCP method, two datasets with various DNN architectures are tested, and the results demonstrate that the AFLCP approach outperforms the baseline method in terms of both communication cost and model accuracy.
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