Sugata Sen

Background: Elderly population attitude towards ageing is critical for their adjustment, acceptance of health-related behavior, survival and choices. Their attitude influences how they cope with the challenges experienced while ageing, which affects their quality of life and health-related outcomes. This study examines the comparison of the attitude of elderly population residing at old home and home dwelling elderly population. Methods: A cross sectional descriptive study among elderly population aged 60-80 years was conducted in a selected old age home and elderly residing at Chennai, TamilNadu. The study participants (40 old age home residents and 40 home residents) were selected using a purposive sampling technique. Data was collected by interview method using Attitude to Ageing Questionnaire (AAQ) in three domains (psychosocial loss, physical changes and psychological growth). Collected data was analyzed based on the objectives of the study using SPSS 23. Results: A total of 80 elderly populations (40 old age home residents and 40 home dwelling) were selected for the study. The mean age was 42.5 ± 9.3 and 30.0 ± 7.6. Majority (62.5 % and 45.0 %) were males. Overall, home dwelling elderly population had a better attitude to the ageing process in all the domains compared with old age home residents.(psychological growth 32.5/40 ± 3.4 Vs. 35.4/40 ± 3.3, p = 0.30; physical change 27.5/40 ± 5.1 Vs. 36.9/40 ± 5.0, p = 0.03; and psychosocial loss 25.3/40 ± 5.7 vs. 28.0/40 ± 5.3, p = 0.60). The overall domains score was 85.3/120 ± 7.2, p = 0.42 Vs 100.3/120 ± 9.5, p = 0.62. Conclusions: The environment in which elderly individuals live significantly shapes their attitudes towards ageing. Ensuring supportive, respectful, and enriching environment is crucial for fostering positive attitudes towards ageing. Care and interventions should be tailored to address the specific needs of both groups, promoting social integration, healthcare access, and economic stability to enhance their overall quality of life.

The study applied growth pole strategy to improve rural quality of life (QoL) in Ogu/Bolo LGA, Rivers State. The stated objectives were to describe the socioeconomic conditions of inhabitants of the study area, identify resources and sectors that that will promote the application of growth pole strategy, identify and evaluate needs of the inhabitants through Needs Assessment and sectors recommendations, and develop policy framework (15-year plan) for the application of growth pole strategy to improve rural quality of life. The study adopted Mixed-Methods Research (MMR) approach and concurrent triangulation research design. Judgmental and simple random sampling techniques were applied to determine the sample size and data collection using 10% precision level. A total of 100 respondents (household heads) were interviewed for the study. The study found that most households attained secondary/technical vocation completed, primary school completed and primary school uncompleted, are traders/businessmen, civil servants and technicians/artisans earning N18,001-N30,000, less than N18,000 and N30,001-N60,000. The study identified 6 sectors (land development and administration, transportation, infrastructure and services, environment, community development, and economy and commerce) and 26 sub-sectors as priority areas to employ growth pole strategy to improve rural QoL in the LGA. The study proposed 1 growth centre and 2 growth districts for concentration and diffusion of growth and development to other peripheral settlements with governments, private sector, international donor agencies, communities and individuals as stakeholders to implement the proposed policy framework. The study further recommended, regional planning studies should be a regular activity in the LGA to identify, harness resources and priotise development needs, the policy and development framework proposed should be followed to articulate both human and natural resources and other capitals, proper utilisation, equitable redistribution and management of resources to reduce inequality gaps, balance growth and develop, and promote partnership between the public and private sectors and international development agencies in the LGA for rural planning and development.

Currently the entire world is grappling to survive from challenges posed by COVID 19 infection. Economies are strategizing and implementing varied responses to curb the menace. World economies are initiating measures to enter the recovery or revival phase. It is recovery from a deep crisis caused by containment measures and subsequent huge contraction in global demand. In the world of networked supply chains this contraction has resulted in further cascading effects, questioning the very sustainability of economic activities.
ILO has already sounded that the pandemic induced economic and social disruption is set to threaten the long term livelihood and well being of millions, especially of the workers. On a very initial observation they have found that nearly 76 percent workers in the informal economy alone have been impacted by the pandemic. It estimated that their income has declined by 60 percent. As a whole the pandemic can wipe out 6.5 percent work hours worldwide creating a further unemployment of 195 million jobs.
But the distress and miseries are not uniform in nature across different vertical and horizontal heterogeneities within the labour force. Observations from different planes have disclosed dichotomous outcomes from different strata. The effect is different between the developed and developing world, formal and informal activities, capital intensive and labour intensive jobs, blue collared and white collared employments, male and female workers, urban and rural residents, excluded and non-excluded groups apart from many others. The intersectionalities among these strata have projected a darker conclusion.
This announcement calls for original research work from the intending contributors for an edited book on the broad theme of direct as well as indirect effects of pandemic on labour economy. This contribution can include model building, empirical work or replication research with sound methodology written in English. The collection is expected to be published from a reputed international publisher.

Submission deadline: 31 JAN 2021

Caste-based exclusion is a manifestation of systematic exploitation of the ruled by the ruler in the name of genetic differences. Exclusion appearing out of genetic differences can be termed as a type of cultural exclusion. This study wants to know the historical sequence of political economy to develop caste as a major tool of exploitation. The existence of this type of exclusion in India is wanted to be substantiated here through the idea of Genetic Algorithm (GA) and Hamming Distance (HD). Policy proposals towards an inclusive society is developed with the help of Knapsack constrained maximization.
As exclusion can be explained as capability deprivation this study has taken into consideration health, education and income as the domains of exclusion. Here the sample size is 320 and data are collected through questionnaire based primary survey. Collected data are used to apply GA, HD and Knapsack optimization.
Appears that caste-based exclusion in India originated in Vedic age through Brahmanical Social Order. HD observes that interpersonal variations in inclusion status on the basis of cultural and genetic differences are remarkably striking. It also comes out that the exclusion gap reduces with successive hypothetical genetic iterations. Knapsack optimization observes that the level of inclusion becomes constant after a certain level of policy mix-the increase in the number of development parameters fails to enhance the level of inclusion after a certain stage. Crossovers among the development programmes in the existence of resource limitations can increase the level of inclusion but cannot completely wipe out the menace of exclusion..

UNDP Rio +20 summit in 2012 evolved a set of indicators to realise the targets of SDGs within a deadline. Measurement of the performances under these goals has followed the methodology as developed by UNDP which is nothing but the simple average of performances of the indicators under different domains. This work concludes that this methodology to measure the goal-wise as well as the composite performances is suffering from major shortcomings and proposes an alternative using the ideas of artificial intelligence. Here it is accepted that the indicators under different goals are interrelated and hence constructing index through simple average is misleading. Moreover the methodologies under the existing indices have failed to assign weights to different indicators. This work is based on secondary data and the goal-wise indices have been determined through normalised sigmoid functions. These goal-wise indices are plotted on a radar and the area of the radar is treated as measure under composite SDG performance. The whole work is presented through an artificial neural network. Observed that the goal-wise index as developed and tested here has shown that the UNDP as well as NITI Aayog index has delivered exaggerated values of goal-wise as well as composite performances.

Ensuring a sustainable livelihood to the larger counts of the population is the most challenging agenda to any developing economy. So this work wants to quantify the level of under achievements of different economies in the field of sustainable livelihood. The contribution of influencing variables on under-achievement and contributing variables to achievement in the construction of under achievement livelihood space is computed under this work. The interaction between these two sets of variables and their juxtaposed effects are evaluated through the use of artificial neural network. Finally this method of artificial intelligence is used to identify a self-sustained monotonic rate of development in sustainable livelihood. The whole model is presented through a set-theoretic neural network. Finally, the developed model is tested over the available secondary data.
This work is based on secondary data published by reputed institutions like World Bank, UNDP etc. Sustainable livelihood is determined through the domains published by Department of Foreign and International Development, UK. The under-achievements in the livelihood are determined through radar presentations. Eventually the economies within the livelihood space are clustered on the basis of their under-achievement radars. These clusters are used to determine the intensities of spatial and histo-logical influences on the under-achievements of different economies. Statistical tools are used to trace the significance of different influencing variables and component variables. Finally the influence of different influencing factors on the clusters are determined and presented diagrammatically. The idea of Artificial Neural Network is used to come to the conclusion. The cyclical causal relationship between the influencing variables and contributing variables is also estimated.
It is found that the under achievement of the economies on sustainable livelihood varied largely. It is observed that the number of economies in a cluster is inversely related to the relative position of that cluster in the hierarchical distribution of clusters. A pictorial illustration of the cluster wise distribution of different economies though projected an interesting diagram but failed to depict any historical or geographical pattern. It is found through regression that adult female literacy rate, balance of payment, human rights and perceptions about corruption have significant effects on under achievement in sustainable livelihood. On the other hand cluster wise determination of influence of component variables on under achievement finds that human capital, social capital and natural capital simultaneously play an important role over almost all the clusters to sustain human livelihood. Simultaneous improvement of all these capitals is necessary for sustainability of livelihood. Finally and interestingly it is found that a push on any set of variables - influencing variables or contributing variables can create cyclical causal movements and create infinite loop of development to sustain human livelihood.