Social Indicators Research最新文献

Women’s empowerment programs play a critical role in achieving the United Nations’ (UN’s) sustainable development goal of “Gender Equality”. However, non-profit organizations (NPOs) running women’s empowerment (WE) programs face challenges in monitoring, assessing, and evaluating the social impact (SI) and program performance due to the lack of solid guidelines. This study aims to analyze the impact and outcome evaluation indicators of WE programs by providing a quantitative tool. A multi-criteria decision-making (MCDM) model is proposed to identify and prioritize the performance indicators by utilizing Fuzzy TOPSIS (FTOPSIS) and Fuzzy AHP (FAHP) in a combined methodology. Results validated the identification and classification of the indicators by their importance and viability. In a qualitative study with NPOs working on WE in Turkey, social impact and outcome evaluation indicators are defined and ranked by criteria set in the proposed combined MCDM framework. The study aims to contribute to the theoretical frameworks and practices on social impact and outcome evaluation of women’s empowerment.

Increasing residential mobility is said to challenge existing social support systems as mobility raises geographic distances between family members. Since family social support is essential for health and well-being, this study investigates whether residential mobility affects familial social support following changes in proximity to family and kin. By applying a stepwise linear regression on data from the German Socio-Economic Panel study, this paper is looking at variations between different residential mobility trajectories regarding social support provision and spatial proximity to family members in Germany over a 10-year period. Our findings show that people who are moving within Germany are receiving significantly more social support from their family and kin, while internationally mobile respondents receive less compared to non-mobile people. Mediation analyses show that proximity to family and kin are accounting for the negative effect of international mobility on social support but cannot explain the positive effect of internal migration.

In recent times, observers have noticed that people with intellectual disability (ID) experience increasing complexity in their older age. Many initiatives launched by healthcare organisations and government bodies are rigorously working to improve ID people’s quality of life (QoL) and health status. The concept of QoL is rooted in a multidimensional framework comprising both universal (etic) and culture-bound (emic) components. It has objective and subjective features and is affected by individual and environmental factors. The professionals in QoL proposed eight dimensions to cover every aspect of ID people, including emotional well-being, interpersonal relationships, material well-being, personal development, physical well-being, self-determination, social inclusion, and rights. In the last decades in Catalonia, the professionals suggested the GENCAT scale predict these eight dimensions’ values through a set of questionnaires containing 69 questions. The professionals use the beneficiary’s response the heir to 69 questions based on four point frequency scale. The GENCAT scale tool converted these 69 questions’ answers into eight values corresponding to the eight QoL dimensions. The GENCAT tool uses a set of rules and some correlatable tables to evaluate the eight dimensions of each beneficiary. In this work, we propose using machine and deep learning-based models instead of the GENCAT tool to estimate the eight dimensions values. Based on the private Newton One dataset, we train various machine learning (ML), such as Random Forest and Decision Trees, along with Deep Neural Networks (DNNs) models to predict the eight dimension values. The trained models predict the eight values by feeding with the 69 questions responses of the beneficiaries. We evaluate the performance of the various models using the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and (R^2) scores. The proposed model based on DNNs achieved the best results among all tested models with MAE of 1.5991, RMSE of 3.0561, and (R^2) of 0.9565. The study shows the promise of the machine and deep learning-based models, particularly DNNs, as a more effective and precise substitute for the GENCAT scale for calculating the eight dimensions of QoL in people with ID. The results open the door for better QoL evaluations and individualised interventions to improve this population’s well-being as they age.

Assessing industrial heritage adaptive reuse projects as a dynamic process in a broader social context such as a neighboring community facilitates a better understanding of their effects. The present study addresses this issue using a cross-lagged model and focuses on perceived safety and social cohesion as two aspects of social sustainability. From 2017 to 2022, 230 participants residing near the “Innovation Factory” project in Mashhad, Iran, participated in a four-wave longitudinal study. The results of paired sample t-tests showed a considerable decrease in perceived safety after the project opening and identified this time point as a weakness that threatens the surrounding community. However, increased social cohesion and perceived safety after renovation compared to before affirms that the occurrence of temporary social deterioration does not necessarily signify long-term social costs. Un-gating an industrial heritage area can provide green spaces, thereby increasing the potential for spontaneous interactions and fostering social cohesion. Comparing models with diverse hypothesized patterns of connections between perceived safety and social cohesion affirmed that the reciprocal effects model has better-fit indexes. This transactional relationship indicates that the two studied variables are interdependent and accumulating concepts, each having a predictive impact on the other.

Abstract

The Covid-19 pandemic has exerted enormous economic stressors on garment workers in the form of income decline, furlough, and layoffs, affecting their families. However, research on family resilience among garment workers is limited, particularly in Indonesia. This study examines the factors associated with the resilience of garment workers’ families. We used a complementary mixed-methods approach to analyze data from the 2021 Family and Community Resilience Survey. To enrich the study, we also performed 23 in-depth interviews and two focus group discussions in Bogor and Bandung Regencies. We assess family resilience as their current status in resolving their most disruptive stressor. We fitted a multinomial logistic regression model and assessed the relative variable importance, with socio-economic characteristics, social assistance, and family organizational factors as groups of explanatory variables. Less than half of the families (46.67%) overcame their most significant stressor. Regression analysis shows that wealth index, cash assistance, and role in the family are the three most contributing variables. Qualitative results underscore the importance of economic resources or access to cash assistance during the Covid-19 pandemic. However, reliance on Emok Bank or other informal lenders can create new stressors due to their high-interest rates. This option is common among garment workers, who usually cannot access the government’s assistance as many are migrants. The study emphasizes the need to strengthen formal social protection systems, especially for vulnerable populations like garment workers, to protect them from future crises.

We propose a novel approach to retirement risk and its measurement. We define retirement risk as a shortfall of financial resources to meet the needs of a retiree’s household, which is different from the inability to maintain a standard of living in retirement. Taking a subjective approach to risk, we operationalise it using the Leyden approach to estimate the minimum satisfactory income for a retiree household and compare it to the pension value. Using a logistic regression model, we estimate the effect of pension value and household and reference person characteristics. The retirement risk level strongly depends on the pension value, household composition, and the reference person’s education attainment level, which also moderates the impact of the pension. This paper contributes to the literature by proposing a subjective retirement risk measurement method and offering a methodological tool that can be used with similar data from other countries.

Abstract

This article studies the importance of the loss of family ties and its symbolic burden in the narrative of homeless people in familistic societies. The family is the main reason why poverty does not directly lead to social exclusion in southern European countries. However, the economic crises of the last two decades have weakened the ability of the family to protect its members. The new forms of poverty that imply processes of individualized social exclusion that lead to homelessness in southern Europe can be understood as a consequence of the overload currently suffered by families in those countries due to the recent economic crises. The loss of family ties in this type of society is so stigmatizing that, even if the person is living on the street for structural reasons such as having been unemployed and having lost their home due to the effects of the recent economic crises and not receiving aid from social services, always reproduces a characteristic story of self-victimization and mourning for not having had a good family that has helped him in times of need.

The outcome of economic growth is visualised as the well-being of citizens or human well-being (HWB). However, it has been a great challenge to measure HWB. Though there are known reasons for considering GDP and its growth as a measure of overall development and progress of nations, yet mostly it is being used as a gospel indicator to compare nations and design appropriate policies. This paper is an effort to develop a comprehensive adjusted GDP to measure HWB through secondary data for thirty years (1990–91 to 2019–20) in India. We make thirty-five adjustments to net national income (NNI) to compute the adjusted national income (ANI) index based on the system analysis approach. The empirical findings show that the gap between NNI and ANI has been growing over time, and the ANI index shows an increasing trend. Through the analysis it is suggested that economic growth should be focused only if it improves HWB (full or partial). The paper attempts to make intervention into policy shift for improving HWB vis-à-vis happiness of people.

People with disabilities are at a higher risk of loss of work, salary, independence, and thus economic self-sufficiency. The research focuses on the possibilities of implementing the inclusive organizational behavior (IOB) concept in terms of increasing employment of people with disabilities by increasing the scope of remote working for people from this group. The research concerns two aspects related to the challenges for IOB in this area: examining the factors on the side of the employee with special emphasis on features that are important from the perspective of performing remote work, and showing the significance and importance of IOB as an element for narrowing the disability employment gap (DEG) and increasing the inclusion of people with disabilities through their employment (including remote employment). The study uses a macroeconomic approach and was carried out on a macro scale using aggregated data for European Union countries. The regression analysis method (multiple linear regression) was used in the research. The results of the research confirmed the different predictors (in the group of examined factors) of the employment rate in groups of persons with and without a disability. In the first stage of the research, significant predictor was found for the employment rate among the group of factors on the side of the employee that influence the remote work of people with a disability—this was the basic or above basic overall digital skills. However, in the group of people without a disability the predictor was found to be the level of education. Expanding the set of previous factors to the disability employment gap in the second stage of the research changed the significant predictor of the employment rate in the group of people with a disability, but did not change the predictor in the group of people without a disability. In the second stage, the significant predictor of the employment rate proved to be the disability employment gap (among others influenced by inclusive organizational behavior) in the case of people with a disability, and—similarly to the first stage – level of education in the case of people without a disability.

Abstract

This paper evaluates the potential of a common unemployment insurance scheme for the Economic and Monetary Union (EMU-UI) to improve income protection of atypical workers, namely those in part-time and temporary contracts. Our approach relies on simulating entitlements to national unemployment insurance and the EMU-UI to assess their effects on the household disposable income of atypical workers in the event of unemployment. Our results show that the introduction of an EMU-UI would reduce coverage gaps and increase net replacement rates, especially for atypical workers, and would protect a large share of the workforce against the risk of poverty. Extending eligibility for the EMU-UI to the self-employed would further improve income protection, reducing their risk of falling into poverty in the event of unemployment.