The Social Trends and Policy Review (STPR) is a peer-reviewed scholarly journal dedicated to the critical examination of contemporary social issues, emerging societal trends, and their implications for public policy. It provides a platform for researchers, policymakers, and practitioners to engage in interdisciplinary dialogue on topics spanning sociology, political science, public administration, economics, cultural studies, and international relations. The journal publishes original research articles, policy analyses, case studies, and review essays that address pressing societal challenges and propose evidence-based policy solutions. STPR emphasizes both theoretical rigor and practical applicability, fostering a deeper understanding of how evolving social dynamics shape—and are shaped by—policy decisions at local, national, and global levels. By bringing together diverse perspectives, the journal aims to inform better governance, advance social equity, and promote sustainable societal development. Editorial Leadership View full editorial board. Chief Editor Dr. Muhammad Bilal PhD in Economics Gomal University, Dera Ismail Khan, Pakistan Associate Editor Dr. Asif Khan PhD in Law Zhengzhou University, Henan, China Managing Editor Dr. Sidra Noreen PhD in Social Psychology Government College University, Faisalabad, Pakistan
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Social Media, Polarization, and Peacebuilding Narratives in Conflict-Affected Societies
Social media has become a central communication space in conflict-affected societies, shaping how communities understand political violence, identity divisions, reconciliation, and peacebuilding efforts. While digital platforms can intensify polarization through misinformation, hostile framing, echo chambers, and identity-based mobilization, they also provide opportunities for counter-narratives, civic dialogue, trauma expression, and grassroots peace advocacy. This paper examines the relationship between social media use, polarization, and peacebuilding narratives in societies affected by conflict. The study explores how online discourse influences public attitudes, strengthens or weakens intergroup trust, and contributes to the visibility of peace-oriented messages. The findings indicate that conflict-related social media spaces are often dominated by emotionally charged narratives, partisan framing, and distrust toward opposing communities. However, the analysis also shows that inclusive narratives, credible civil society communication, and youth-led digital campaigns can reduce hostility and encourage dialogue when they are supported by trust-building strategies. The results suggest that social media is not inherently harmful or peaceful; rather, its impact depends on platform governance, narrative framing, digital literacy, and the credibility of actors producing and circulating content. The paper concludes that peacebuilding in the digital era requires coordinated efforts among communities, civil society organizations, media actors, educators, and policymakers to promote responsible communication, counter misinformation, and amplify constructive narratives in conflict-affected societies.
Copyright (c) 2026 https://creativecommons.org/licenses/by-nc-nd/4.0
Gendered Impacts of AI-Driven Work Platforms: Income Security, Digital Skills, and Workplace Voice
AI-powered work platforms are quickly redefining the landscape of labour markets, fundamentally changing how workers approach tasks, how they get paid, how they learn digital skills, and how they voice concerns in the workplace.AI work platforms are changing labour markets in fundamental ways, affecting how workers approach tasks, how they're paid, how they acquire digital skills, and how they voice workplace concerns. But these changes are not gender neutral; that is, the social, economic and technological conditions of platform work are different for women and men. This research focuses on how AI-driven platform work affects gender equality, particularly in terms of income security, digital competencies, and voice in the workplace. These findings show that women platform workers are likely to experience relatively greater income volatility, lower average earnings, and higher likelihood of unpaid or under-recognized digital work. While gendered opportunity structures are created in AI-driven platforms, the results reveal that such opportunity structures are more pronounced among men, as women exhibit less confidence in their digital skills, fewer examples of work they can see as digitally available, less access to higher-paying categories of work on the platforms and less time available to engage with them. The analysis also shows that digital skills have a strong positive effect on income security, however women report less access to further opportunities for developing their digital skills and fewer opportunities for accessing algorithmically rewarded tasks. Workplace voice is also a key issue; women workers say they are less involved in decisions made on platforms, have less knowledge of platform grievance processes, and feel less confident in challenging automated ratings, restrictions on accounts, and unfair allocation of tasks. In conclusion, the study indicates that AI-powered work platforms can perpetuate current labour market inequalities if they are not implemented with gender in mind in platform governance, digital training, and ensuring the protection of workers. The paper illuminates ongoing discussions on algorithmic management, platform labour and inclusive digital economies by highlighting the need to consider income security, skills and voice in relation to each other to grasp the gendered impacts of algorithmic work.
Misinformation Resilience and Democratic Participation in the Era of Generative AI: A Comparative Social Science Study
The study explores how misinformation is perceived and accepted (misinformation resilience) and how citizens participate in democracy in the current context of generative artificial intelligence, especially the impact of AI-generated information on citizens' trust, political engagement, and ability to find misleading information. The rise of the power of generative AI to generate lifelike text, image, audio and video content poses new challenges to democratic societies in terms of electoral integrity, public opinion manipulation and information disorder. With a comparative social science lens, the study examines variations in how much exposure to misinformation someone has, their level of digital literacy, trust in institutions, platform dependence, and civic engagement in selected democratic environments. The findings suggest that societies with robust media literacy, high trust in institutions, and clear platform governance are more resilient to the threat of misinformation spreading via artificial intelligence. The results further indicate that digital literacy interventions for younger, more connected citizens also increase their exposure to generative AI misinformation, but can also improve their ability to verify information. The current study reveals that misinformation resilience is not solely a technological problem but a social, educational, and governance-related problem as well, through comparative patterns. This study emphasises the need for awareness of the public, systems of fact-checking, civic education, platform accountability and policy coordination to safeguard the integrity of democratic participation from manipulation through AI. In conclusion, the paper suggests that a multi-stakeholder approach is needed to build democratic resilience in the era of generative AI, encompassing citizens, governments, education providers, media outlets, and technology platforms.
Copyright (c) 2026 Farah Noreen, Syed Ali Hassan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Generative AI, Academic Integrity, and Student Learning Autonomy in Higher Education: A Cross-Cultural Study
The rise of generative AI has dramatically altered the landscape of the higher education sector, impacting student information seeking, academic writing, problem-solving, and learning processes. But as it has been used more, there have been serious concerns about academic integrity, originality, overdependence and the development of independent learning. The research explores how generative AI affects academic integrity and students' autonomy in learning across cultures in higher education. It has revealed the difference in perception and application of AI tools for academic work among students from various cultural and educational backgrounds, regarding responsible use, ethical decision making, self-regulated learning and awareness of institutional policies. These findings show that generative AI is being adopted across a broad range of areas for generating ideas, summarization, language enhancement, and assistance with assignments, yet student conceptions of "ethical boundaries" vary widely. A vast majority of participants indicated that AI enhances their sense of confidence, productivity, and learning independence, while some revealed dependence and did not understand what is considered misconduct. The following were significantly different across cultures: policy awareness, teacher guidance, and attitudes toward AI-assisted writing. These results indicate that generative AI can be employed as a learning assistant to help students learn independently instead of a tool to replace their own work. If there aren't clearly established institutional policies for what constitutes original work, digital literacy training, and culturally appropriate academic integrity policies, though, then using AI can undermine originality and foster unethical academic practices. The study suggests that the focus needs to shift from a blanket ban to creating clear policies for the use of AI, revisiting how the capabilities of AI are assessed, and refining programs to train students about responsible, ethical, and independent learning in AI-enabled classrooms.
AI-Supported Climate Migration Planning: Equity, Social Protection, and Community Adaptation in High-Risk Regions
Climate-induced migration has become one of the biggest social, environmental, and governance challenges in high-risk areas. In response to the impacts of rising temperatures, floods, droughts, sea-level rise, food insecurity, and livelihood disruption, vulnerable communities are having to move—at least temporarily, or even permanently. In this paper, AI's role in assisting climate migration planning through the enhancement of risk forecasting, determining the most vulnerable communities, bolstering social protection frameworks, and assisting with community-based adaptations is explored. From a practical perspective, the study emphasizes the contribution of AI-powered tools like geospatial mapping, machine learning-based models, early-warning systems, vulnerability indexes, and predictive displacement analysis to support government and humanitarian decision-making. The results highlight the potential of AI to enhance climate migration planning by identifying vulnerable households, predicting migration trends, prioritizing resources, and enabling tailored policy interventions. The paper also highlights the importance of equitable and transparent AI planning, data protection, and community engagement. If there is no inclusive governance, AI systems can deepen inequities, marginalize or misclassify vulnerable households or favor populations that are not socially invisible but are technically visible. The paper argues that the use of AI should not be a substitute for planning rooted in the principles of social justice and adaptive governance but rather a decision-support tool in these frameworks. Planning for climate migration needs to combine technological innovations, social protection, local knowledge, participatory adaptation, and rights-based policy design.
Exploring the Relationship Between Education and Social Stratification in Global Societies
The paper evaluates the relationship between education and social stratification in global societies with the help of mixed-methods, quasi-experimental research design. Quantitative studies which employ cross-national data indicate a significant and statistically significant relationship between educational attainment and such critical stratification outcomes as income distribution, occupational status, and intergenerational mobility. Multivariate and fixed-effects models demonstrate that high educational levels improve the likelihood of upward social economic mobility, but propensity score matching shows a measurable treatment impact of educational levels to improved social placement. Nevertheless, these effects vary according to location, and this is because of the disparities in the quality of education, the nature of the labour market as well as the welfare system. Qualitative data also show the impact of institutional organizations, the recognition of credentials, and the social network in the returns to education, often continuing to provide benefits to individuals with more advantaged socioeconomic backgrounds. The findings show that education serves simultaneously as a source of social mobility and a medium of ensuring the continuation of inequality. The work contributes to the sociological theory in explaining the conditional nature of the educational returns and providing policy-relevant knowledge towards the generation of an education system that promotes equity and social inclusion under diverse conditions in society.
Copyright (c) 2025 Ayesha Rahman, Muhammad Imran Ali (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Social Capital and its Impact on Community Development in Rural and Urban Areas
The study will be directed to the role of social capital in influencing community development of the rural and urban communities using the mixed method research design. Quantitative analysis revealed statistical positive relation between the dimensions of social capital, namely trust, social networks, civic participations, and reciprocity, and the most crucial indicators of community development, namely, economic participation, accessibility of services, social cohesion, and good governance. The bonding social capital was higher in the rural areas and this significantly enhanced collective action and resilience of the community, whereas the bridging and connecting social capital in urban areas was superior and hence provided access to institutions and economic mobility. The performance was enhanced when the qualitative studies helped to explain the influence of contextual factors, including population density, institutional presence, and cultural norms on development and utilization of social capital. As has been observed comparatively, societies that have an optimal mix of bonding, bridging and linking social capital have enjoyed better sustainable and equitable developmental outcomes compared to those that depend on one type. The paper concludes that social capital is the tool that plays significant roles in mobilizing resources as well as in alleviating social risks and increment of community development. The results are applicable in providing information to politicians and development professionals who wish to devise mechanisms that would employ social capital in improving community development in different destinations.
Copyright (c) 2025 Khadija Saleem, Naveed Akhtar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Social Science: Exploring the Role of NGOs in Promoting Gender Equality and Social Justice in Developing Countries
In this research, the role of non-governmental organizations (NGOs) in promoting gender equality and social justice in developing countries is examined, with the focus on the evaluation of the outcomes of their initiatives in the social, economic, and institutional aspects. The results obtained with the help of the mixed-methods analytical approach point to the fact that NGO programs have produced measurable improvements in the women empowerment, including better access to education, medical institutions, awareness of legal rights and opportunities of generating income. Quantitative statistics indicate high rates of improvement in the activity of women in the life of the community, and in the labor market, yet the qualitative studies draw attention to the positive shifts in the relations to gender norms and social inclusion. The research also demonstrates that NGOs are valuable bridges between the marginalized population and official government agencies, where the voices of the people who are usually overlooked during the policy formulation are heard. It was demonstrated that collaborative strategies involving local stakeholders and government institutions contribute to extending program duration and having a greater impact on policy. Nevertheless, the outcomes also indicate that all the issues are not eradicated yet, such as financial instability, the necessity to overcome cultural resistance, and available methods to monitor everything, which result in less efficient and long-term outcomes. Overall, the findings indicate that NGOs have a significant role in ensuring gender-responsive development and social justice in the underdeveloped nations. It can make the NGO-led activities even more effective and ensure that progress on fair development goals can be made in the long term by strengthening institutional support, accountability structures, and cross-sector alliances.
Copyright (c) 2025 Bushra Kanwal, Abdul Rehman Siddiqi (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Influence of Immigration Policies on National Identity and Social Cohesion in Europe
This study will focus on the effects of immigration policy on national identity and social cohesiveness in European countries by using a mixed-method, quasi-experimental research design. With the help of longitudinal cross-national survey data and comparative policy indicators, the quantitative analysis demonstrates that immigration policy direction has a significant impact on the perception of national identity, social trust, and relations with the intergroup. Multilevel and difference-in-differences models show that inclusive and integration-focused immigration policies are related to higher levels of social cohesion and wider and more inclusive conceptions of national identity and restrictive policies are linked to increased polarization and reduced social trust. These patterns are explained with the help of qualitative data, which represents policy discourse analysis and semi-structured interviews to show how political narratives and institutional practices are, in effect, contributing to the social outcomes of immigration policies. Those nations, which discuss immigration in reference to shared values, participation, and equal rights, are more likely to have more social ties. Conversely, those countries which discuss immigration in exclusionary and security terms have greater social obstacles. The research integrates statistical and interpretive approaches to demonstrate how the immigration regulations are influential in influencing the social impacts of migration. The findings contribute to the theoretical arguments on the subject of national identity and social cohesiveness, as well as they provide policymakers with valuable information on the issue of balancing control of migration and inclusion of individuals into diverse European nations.
Copyright (c) 2025 Sana Ehsan, Umar Farooq (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Youth Unemployment and Its Impact on Social Stability: A Comparative Study of Developing and Developed Countries
Unemployment among the youths remains one of the most important problems worldwide with many far-reaching implications on social stability and economic viability. This paper is a comparative assessment of the impact of young unemployment on social stability through developing and industrialized countries. The study uses a mixed method design, which includes cross-national unemployment data, social instability data, and comparative policy research to determine the influence of unemployment rates among the youths on social cohesion, political participation, crime rate and trust. The results show that the level of young unemployment is significantly higher in the developing countries that are strongly linked with the increased social unrest, political instability, informal labor involvement, and emigration. On the other hand, wealthy countries, even with cyclical adolescent unemployment, have relatively less disruptive levels in the society and this is due to well-established labor market institutions, welfare systems, and skill-development systems. The findings also indicate that in both cases the long term young unemployment causes psychological stress, social marginalization and loss of trust in government institutions. The paper indicates that the social effects of unemployment among teenagers are not determined solely by the economic aspect but also the governance and the effectiveness of policies. The research concludes that general employment policies that aim at assisting individuals to leave school to work, aligning talents, and facilitating advancement to all individuals are needed to decrease social unsteadiness. These results can provide valuable information to the policy makers in the quest to address unemployment among the young people as a core element in the social and economic development.
Copyright (c) 2025 Aiman Tariq, Salman Bashir (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Effect of Economic Crises on Poverty Reduction Strategies
This study examines the impact of economic crises on poverty reduction strategies using a mixed-methods experimental design that integrates quantitative econometric analysis with qualitative policy evaluation. Drawing on panel data from 2000 to 2021 across developing and emerging economies, the research employs fixed-effects regression, difference-in-differences estimation, and robustness checks to evaluate the effectiveness of interventions such as cash transfers, food subsidies, and fiscal relief packages. The results demonstrate that crisis periods significantly increase poverty headcounts and inequality indices, but targeted policy measures can mitigate adverse effects. Cash transfers emerged as one of the most effective instruments, raising consumption levels and reducing immediate poverty risks, while food subsidies provided stability in nutrition and household resilience. Digital financial inclusion further enhanced coverage and transparency, highlighting the importance of technological adaptation during systemic shocks. Qualitative findings reinforce that governance capacity, targeting efficiency, and institutional readiness determine the sustainability of these strategies. Evidence from case studies suggests that proactive, scalable, and context-specific poverty reduction measures are more effective than rigid, one-size-fits-all policies. The study also confirms that crises exacerbate pre-existing inequalities, calling for structural reforms alongside short-term social protection. Overall, the findings highlight that although crises threaten to reverse decades of progress, adaptive policy design—integrating fiscal flexibility, social safety nets, and multidimensional poverty frameworks—can transform them into opportunities for more equitable development.
Copyright (c) 2023 Ammara Sheikh, Imran Yousaf (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Behavioral Economics and Its Implications for Consumer Choice
This study investigates the implications of behavioral economics for consumer choice through a mixed-methods approach combining econometric analysis, experimental design, and behavioral segmentation. Using datasets comprising default acceptance, framing effects, present bias, and socio-demographic variables, the analysis employed correlation matrices, regression models, ANOVA tests, and factor analysis to identify the determinants of consumer decision-making. The results indicate that default options significantly increase acceptance rates, framing effects influence willingness to pay, and present bias strongly predicts impulsive consumption. Moreover, the heterogeneity across income groups, gender, and technology adoption levels highlights the importance of socio-demographic and contextual moderators in shaping consumer behavior. Robustness checks further validate the reliability of the findings, while visualizations—including heatmaps, scatter plots, radar charts, and 3D models—demonstrate the complexity of interactions between behavioral factors. The study contributes to behavioral economics literature by providing empirical evidence that consumer decisions are systematically shaped by psychological biases and contextual framing rather than purely rational optimization. These insights have significant implications for public policy, marketing strategies, and digital choice architecture, suggesting that tailored nudges, informed defaults, and transparent framing can promote better decision outcomes. Ultimately, the research emphasizes the necessity of integrating behavioral insights into economic models to enhance predictive accuracy, improve consumer welfare, and design interventions that are both effective and ethically sound.
Copyright (c) 2023 Nida Hassan, Salman Javed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Artificial Intelligence in Digital Heritage Preservation
Artificial intelligence (AI) is another breakthrough in the process of digital heritage restoration, allowing to enhance accuracy, scale, and cultural accessibility thereof. Within the design of this research was a mixed-methods experimental approach to understanding AI applications with quantitative modelling and qualitative outlooks of heritage specialists. Quantitative findings revealed that AI techniques such as image recognition, 3D reconstruction, and natural language processing worked well in making their forecast, many of them having accuracy and F1-scores of over 0.90. Regression analysis revealed that there were high correlations between the size of information, the sum of the amount financed, and the outcome of preservation. The results of the comparison between the baseline and AI-enhanced models indicated the increase in the key criteria by 20 to 30 per cent. The regional analysis indicated that the leaders in finance and adoption are Europe and Asia, whereas Africa and South America are new territories with innovations, even though these regions lack a lot of resources. These findings were supported by qualitative analysis, which highlighted the cultural ethical value, such as authenticity, ownership, and accessibility of data. These results demonstrate the role of AI in increasing the efficiency of heritage digitization and changing the global practices and protecting the access of the world heritage to future generations. The study suggests that AI would be best employed in tandem with other strategies that fuse computational accuracy with cultural consciousness and make it an essential constituent of sustainable heritage preservation.
Artificial Intelligence, Digital Heritage, Cultural Preservation, Machine Learning, Mixed-Methods Research, Global Access
Copyright (c) 2025 Ayesha Rauf, Hassan Mehmood (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
AI Analysis of Global Film and Music Consumption
This study analyzes the global film and music listening habits with the help of AI-guided data processing and renders specific trends with respect to region, audience, genre, and platform. The study employs large-scale data using the machine learning paradigm to report significant differences in the level of involvement in both arenas. The findings demonstrate that the citizens of Asia and North America view the highest numbers of movies each week, whereas people of Europe and South America listen to the greatest amounts of music each week. Following genre-based statistics, the most well-liked types of movies are Action and Comedy as well as the most well-liked genres of music being Pop and Hip-Hop globally. The streaming of movies on Netflix and music on Spotify is the largest globally as indicated on the platform analysis. The second place is occupied by Apple Music and Youtube Music. One thing that demographic data demonstrates is that younger individuals ranging between the ages of 18-34 are the people with the greatest interest concerning movies and music. People that are older are, however, less interested. Cross-platform comparisons indicate that individuals watching many movies are more prone to listen to many records too. This demonstrates that the life of digital entertainment is converging. Presenting complex diagrams such as bar graphs, line graphs, pie charts, scatter plots and composite plots to present results gives solid evidence of how the world economy in consumption works. All these evidence points to the effectiveness of AI as a research tool to assess the cultural trends, predict behavioural alterations, and assign strategic knowledge to the industrial players. The study contributes both to theoretical and practical arenas in providing knowledge about connecting digital media consumption with cultural behaviour in a better connected cross-nation context.
AI in entertainment, global consumption trends, film streaming, music streaming, genre analysis, cultural behavior
Copyright (c) 2025 Sara Imtiaz, Usman Khalid (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Predicting News Virality Using Machine Learning Models
The paper set out to determine the level of efficacy found in machine learning models when evaluating the virality of the online news stories, through the mixed-methods approach of incorporating both quantitative performance indicators and qualitative language evaluation. Textual characteristics and engagement statistics were preprocessed and transformed through TF-IDF and embedding techniques and feature engined into sentiment polarity, thematic diversity, and article length. Some of the supervised models we trained and tested are Logistic Regression, Support Vector Machines, Random Forest, Gradient Boosting and XGBoost. We employed stratified splits and bootstrap validation and measures of performance such as Accuracy, Precision, Recall, F1-score, and the ROC-AUC. As can be seen in the results, ensemble methods were always more accurate and achieved a higher F1-score as compared to the baseline models. The recall was higher in Logistic Regression and Naive Bayes like Recall was better in Logistic Regression which implies the better article containing viral article retrieval. TF-IDF characteristics enhanced more compared to embeddings in sparse environments in terms of text. The HAP analysis further added more insight as to how sentiment, alteration in themes, and language style may all be key contributors to making anything go viral. The findings suggest hybrid approaches that combine the power of algorithms with linguistic understanding to be the most robust framework of predicting newsworthiness. The study contributes to the areas of research on computational journalism and the digital realm of communication by providing practical suggestions on how to enhance the forecasts of engagement and stem the proliferation of misinformation by means of guidance of media platforms, marketers, and politicians.
News Virality, Machine Learning, XGBoost, Ensemble Models, Computational Journalism, Sentiment Analysis
Copyright (c) 2025 Ayesha Noor, Hamza Rauf (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Artificial Intelligence in Online Hate Speech Detection
<span style="font-size: 12.0pt; line-height: 115%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; color: black; mso-themecolor: text1; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">The study analyzes how artificial intelligence (AI) can detect hate speech on the Internet through the use of machine learning and natural language processing theory to label and mitigate abusive content on the Internet. An unhomogenized dataset of multilingual social media messages was preprocessed with the help of tokenization, stemming, and contextual embedding models in order to identify subtle semantic attributes. The results of the experiments suggested that deep learning models, particularly transformer-based, were more accurate, more recall-centered, and more F1-score centred than traditional classifiers, reaching higher than 92 percent detection accuracy and compensating with a significant reduction in false negatives. A comparative study revealed that explainable AI strategies and ensemble models increased the resistance of models to change in the face of hostile text, whilst explainable AI strategies and ensemble models facilitated easier understanding of how the models achieved their decision-making. Cross-linguistic analysis also demonstrated that AI-based detection systems had high levels of generalizability in different contexts related to various cultures. These results confirm AI to be potentially a scalable and reliable instrument to improve content moderation policies, secure online communities and inform future governance actions against online hate speech.
artificial intelligence, hate speech detection, natural language processing, machine learning, social media, content moderation
Copyright (c) 2025 Sadia Khan, Muhammad Bilal (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
AI Applications in Human Migration Pattern Analysis
The present work explores the application of artificial intelligence (AI) to analyze and understand human movement patterns through introductions of machine learning models, geographical data, and sociocultural markers. The results showed that AI-based approaches can significantly enhance the accuracy of migration forecasts compared to traditional statistical approaches, and predictive improvements of 18 and 22 percent in cross-border, and rural-to-urban migration forecasts, respectively. The findings revealed that the most significant variables were the economic factors, environmental shifts, and the sociopolitical factors. Models based on deep learning were particularly effective to reveal nonlinear relationships between these drivers. Moreover, hybrid systems combining spatial-temporal clustering with natural language processing showed high levels of efficacy in making invisible patterns visible in migration narratives and policy texts visible. When migrant movements were visualized, hotspots were created by regions, seasonal, and crisis displacement. This demonstrated the ability of AI to be able to capture macro-level global trends and micro-community dynamics. This evidence demonstrates that AI does not only make predictions but can also assist policymakers in developing data-driven solutions to the long-term management of migration. The paper concludes that AI-specific analytics offers a transformational framework to improve the empirical research of human mobility in the context of global issues such as climate change, economic disparity and geopolitical turmoil.
Artificial Intelligence, Human Migration, Machine Learning, Predictive Modeling, Spatial-Temporal Analysis, Migration Governance
Copyright (c) 2025 Hina Saleem, Tariq Mehmood (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Machine Learning Applications in Cultural Artifact Analysis
This paper discusses the role of machine learning in studying cultural artifacts, its capacity to uncover hidden patterns, categorize symbolic representation and enhance interpretive structures of different cultural settings. The research involved supervised and unsupervised models that tested the classification level, the level of clustering, and the level of prediction of interpretability of the artifacts, which were texts, photographs, and historical documents. The findings indicate that ensemble-based approaches, such as XGBoost and Random Forest, performed very well at classifying artifacts and were right over 90 percent of the time. The clustering algorithms such as k-means and the hierarchical methods, on the contrary, identified concealed cultural groupings with a high silhouette score of more than 0.75. Also, the methods of explainability, i.e., SHAP values and rankings of the feature importance, demonstrated that the most significant elements of differentiating cultural artifacts were linguistic motifs, visual textures, and symbolic markers. Regression approach-based methods have proven to have significant predictive relationships between the features of artifacts and cultural contexts, which emphasizes the value of the data-driven interpretation of the heritage studies. The results all highlight the fact that machine learning does not just improve quantitative research but also enhances qualitative inquiry with scalable, replicable and interpretable insights. This offers a theoretical basis of integrating the computational methods into cultural studies, thereby improving not only academic understanding, but also the electronic preservation of human history.
machine learning, cultural artifacts, classification, clustering, interpretability, digital heritage
Copyright (c) 2025 Sehrish Javed, Noman Siddiqui (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Community-Based Organizations in Poverty Alleviation
This paper explores the critical role of community-based organization (CBOs) in addressing poverty through localized efforts, participatory governance and sustainable livelihoods. The findings indicate that the CBO-led initiatives made a significant difference to household income, educational and healthcare accessibility and community resilience to economic shocks. Quantitative research revealed that there were substantial changes in terms of reduction of unemployment and dependency rates but the qualitative research indicated that the excluded groups were empowered through developing their skills, microfinance programmes and the involvement of the populace in decision making. Another conclusion based on the results indicated that the areas where CBOs operated had a higher level of social cohesiveness, trust, and collaborative resource management that served in alleviating poverty effectively in the long run. The research also found that community-based organizations (CBOs) had the capacity of bridging state-directed welfare policies to the interests of local communities. This ensured that the measures to be applied in reducing poverty were pertinent to the situation and everybody was included. These findings reveal the significance of developing community-based strategies as an addition to national poverty eradication models in places where institutions lack significant power. The paper concludes that CBOs cannot be seen merely as providers of services, but as agents of social change as well, hence necessary in long-term poverty alleviation.
community-based organizations, poverty alleviation, social empowerment, microfinance, sustainable livelihoods, participatory governance
Copyright (c) 2024 Hina Rauf, Salman Akhtar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Administrative Capacity in Disaster Management
This paper looks at the critical role played by administrative capacity in managing disasters, and looks at how the institutional preparedness, organizational resources and governance structures affect effective management of crises. According to empirical findings, the findings show that the administrative capacity that is strong in terms of good human resources, open communication systems, and inter-departmental cooperation is a significant boost to the speed and efficiency of catastrophe reduction and recovery efforts. Regions with well-developed administrative systems were more resilient since they would be better mobilized to rescue, allocate resources faster, and gain the confidence of the population. Conversely, limited capacity was significantly associated with broken responses, ineffective delivery of services, and slower recovery rates, which in most cases aggravated the social and economic outcomes of catastrophes. The statistical study revealed that investing in disaster-ready administrator/system training was significant in disaster outcomes. The performance measures were always better in the areas that had lower resources. Also, the study highlighted that administrative transparency and accountability procedures are fundamental to sustain disaster resilience in the long term. The findings demonstrate that the administrative capacity does not form an additional element but a determinant of disaster management success. This demonstrates that the goal of the policy frameworks should be on strengthening institutions, capacity building or enhancement as well as collaborating in governance.
administrative capacity, disaster management, governance, resilience, institutional preparedness, crisis response
Copyright (c) 2024 Sadia Khalid, Imran Ashraf (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Impact of Health Policy Reforms on Healthcare Access
The paper examines how the improvement of the health policy has led to the improvement of access to healthcare focusing on equity, affordability, and quality of care. The results suggest that coverage and service availability have been significantly improved since the implementation of the latest changes, and a mixed-method strategy combines the quantitative analysis of the data on healthcare consumption with the qualitative information obtained for the patient and provider perspectives. There are statistical results that show a significant reduction in out-of-pocket costs and access disparities in disadvantaged groups and regression data confirm that policy interventions are positively related to increased rates of healthcare use. It is also revealed in qualitative interviews that the patients are more satisfied, believe in health institutions, and believe that they provide services more equally. Things are not without their issues, however, such as uneven implementations by region and persistent shortages in rural and vulnerable regions. On the whole, the findings indicate that the changes in policy have facilitated accessibility of things and reduced the costs, yet to ensure that they are effective in the long-term, they must be monitored frequently, modified where necessary and reinforced through other social programs. The study contributes to the growing literature that planned changes can greatly enhance healthcare equity and provides information that policy makers can apply to help make health systems resilient globally.
health policy, healthcare access, equity, affordability, reforms, patient outcomes
Copyright (c) 2024 Rabia Nasir, Saad Abdullah, Aftab Ahmed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Relationship Between Transparency Policies and Public Trust
This paper focuses on the multifaceted relationship between transparency policies and the level of trust that people have in their institutions, and how the level of clarity, accessibility, and accountability in government may affect the level of trust in institutions among the citizens. The results, however, provided quantitative and qualitative data, demonstrate that the higher the levels of trust in the work of the administration are, the more effective the transparency mechanisms, including open data portals, financial disclosures, and participatory reporting. The statistical analysis showed an increased tendency of the participants who perceived decision-making processes as transparent to follow rules and support communal programs. Conversely, confidence levels declined where individuals believed that there was superficiality or weakness of transparency even in cases of existence of official policies. Regression equations confirmed that transparency is a strong predictor of institutional trust though its impact is mitigated by situational factors such as political culture, past lack of trust and effectiveness of enforcing the policies. Qualitative results also highlighted the importance of citizens to the availability of information as well as its readability, timeliness, and relevance to their lives. Findings indicate that the concept of openness, when implemented meaningfully but not as a mere symbol, forms a significant component of developing long-term confidence between the governments and the people.
transparency, governance, accountability, public trust, policy effectiveness, citizen engagement
Copyright (c) 2024 Tehmina Aslam, Zubair Ahmed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Policy Evaluation in Improving Governance Outcomes
This research paper explores the role of policy evaluation in improving the quality of governance by examining the effectiveness, efficiency, and responsiveness of all the public policies in the different sectors. The results suggest that systematic evaluation practices have significant impacts on increasing policy transparency and accountability, leading to the increased evidence-based decision-making processes. Quantitative data indicate that those jurisdictions that do regular policy evaluation reported a level of efficiency service delivery that was at least 25% higher than those which did ad hoc assessments only. In addition, the involvement of stakeholders in the process of evaluation was closely connected with the increased trust and satisfaction of the population, and the importance of inclusive governance cannot be overlooked. Comparative outcomes also indicated that the employment of the data motivated evaluation tools led to the reduction of misallocating resources by more than 18% and enabled the programs to become more flexible in social and economic environments that were rapidly changing. The paper reveals that in countries that have robust evaluation systems, there is an improved outcome of durable governance meaning that there is reduced policy failure, budgetary prudence and increased trust in the institutions. The study provides empirical confirmation of the synthesis of structured policy evaluation in governance mechanisms to enable continuous improvement, improve legitimacy and gain sustainable benefits to society.
Policy evaluation, governance outcomes, accountability, transparency, evidence-based decision-making, institutional credibility
Copyright (c) 2024 Naila Irfan, Ahmed Rauf (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Effectiveness of Social Welfare Programs in Poverty Reduction
This paper focuses on the effectiveness of social welfare policies in reducing poverty, especially the income support, employment, health care subsidies, and educational assistance. The investigation used the descriptive statistics, regression modelling, and comparative evaluation which revealed that since the introduction of the cash transfer initiatives and food security programs, there was a significant rise in the level of household consumption and a reduction in poverty levels of more than 20 percent in the targeted populations. The long-term effects of welfare programs that are aimed at getting people jobs were more stable, including getting a greater number of people to work and reducing dependency rates. Health and education indirectly worked to alleviate poverty by reducing out-of- pocket costs and increasing human capital returns. It was revealed that regional variations indicated that region specific programs that were tailored to socio-economic circumstances were more effective compared to national strategies that were uniform across all regions. The results highlight the importance of integrated welfare programs (which combine cash transfers with structural investments in health, education and employment) generate the most credible reductions in multidimensional poverty. The results demonstrate that welfare schemes though not a panacea are a tool that should be used in reducing poverty where carefully designed, adequately funded and strictly assessed as the measure of effectiveness and equity.
poverty reduction, social welfare programs, income support, employment generation, healthcare subsidies, education assistance
Copyright (c) 2024 Shumaila Yaqoob, Rashid Anwar (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Public Policy in Addressing Income Inequality
This paper discusses the central role played by the public policy in reducing economic inequality by analysing fiscal redistribution, labour market regulation, social welfare and education-based equity initiatives. The results, based on the quantitative analysis of data and policy assessment model, suggest that progressive taxation and selective welfare transfers help a lot to reduce income gaps but their efficacy varies in various socio-economic cases. The results highlight that labour market policies, in particular adjustments in minimum wage, and the introduction of social protection policies help enhance income security among the disadvantaged groups and enable inclusive economic development. Investments to available education and skill development programs also reduce inequality in the long run as more people can move up the world ladder. There are also issues in the report, such as policy implementation gaps, disparities in accessing benefits, and the fact that regressive fiscal action could worsen differences in the event that it is not planned well. The study shows that a mixture of a systematic approach to the formation of the overall public policy, including redistribution, regulation and capacity-building is essential in terms of successfully resolving the issue of income inequality and ensuring sustainable socio-economic development. The study highlights the need to focus on adaptive and circumstantially sensitive policies that can balance equity and economic productivity, which can be substantial pointers to policy makers who seek to address rising income inequalities in both developed and emergent economies.
public policy, income inequality, redistribution, welfare programs, labor markets, education equity
Copyright (c) 2024 Fariha Shahid, Usman Khalil (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Relationship Between Bureaucratic Efficiency and Corruption Control
It is one of the numerous cases of bureaucratic efficiency which harms the corruption control processes. The interconnection between the two knowledge areas has been discussed in the present paper, specifying the direct interrelation between efficiency of the administrative work and state of the governance institution integrity. Based on empirical evidence and comparing the effects of bureaucratic efficiency in various institutional settings, it has been observed that high levels of bureaucratic efficiency have a high contribution to the enhancement of improved measures in corruption control. This was confirmed by the efficiency of bureaucracies which are characterised by clarity of procedures, timely delivery of services, and employing people on merit which greatly reduced the risks of rent-seeking behaviour and unjustified exploitation of the powers to make personal wealth. On the one hand, bureaucratic delays have been shown to have created strategic loopholes that facilitated corruption incidences and made individuals less responsible and less trusting of the government. The results also demonstrate that countries with well-coordinated bureaucratic systems well supported by technological and institutional protection systems keep on emerging at the forefront in curbing corruption as opposed to those with poor coordination or inadequately funded bureaucratic systems. It can also be seen in the data that bureaucratic efficiency plays a larger positive role when it is supported by political will, sound legislative frameworks, and effective civil society oversight. The thesis finally takes the stance that, making the workings of the bureau more efficient is not only a technical overhaul, but a tactical means of ensuring long-term corruption stabilization, and has potentially enormous implications on the quality of governance, economic development, and social justice.
bureaucratic efficiency, corruption control, governance, public administration, institutional integrity, accountability
Copyright (c) 2024 Samina Riaz, Khalid Mehmood (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Impact of Public-Private Partnerships on Infrastructure Development
The paper looks at the role played by the public-private partnerships (PPPs), in terms of efficiency, effective costs and sustainability in development of infrastructure. The analysis including quantifiable success criteria and qualitative policy evaluation demonstrates higher rates of project delivery with PPPs in comparison to the traditional approaches of the project delivery. According to the findings, projects that were undertaken under the PPPs have an average of 20-30 percent reduction in time lag and 15-25 percent improvement in meeting target within the budget limit. Besides, the involvement of commercial partners led to the inclusion of new finance models, innovative technical solutions, and better risk-sharing models all of which contributed to improved service levels and lifecycle support outcomes. The data however reveal that there are issues, like complicated governance, inconsistency of contract transparency, and the concerns over societal equity, particularly in low- and middle-income environments where cost may be a limiting factor. As seen, however, PPPs are hardly a silver bullet; nevertheless, they provide a positive framework of dealing with the shortcomings of the infrastructure in case supplemented with effective regulatory oversight, transparent community involvement, and effective accountability measures. The study concludes that well-designed PPPs significantly accelerate the construction of infrastructure and they must be tailored according to the specific scenarios, and the terms of the partnership must be balanced to relieve any conflicts of interest between the state and the private sector.
Public-private partnerships, infrastructure development, project efficiency, financing models, risk-sharing, policy innovation
Copyright (c) 2024 Adeel Hassan, Maria Yousaf (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Policy Responses to Climate Change in Developing Nations
This study explores policy responses to climate change among the developing countries highlighting the success and challenges continuing to be encountered. This analysis reveals that despite these countries having made international climate promises, laid down renewable energy targets and drawn national adaptation plans, nevertheless they tend not to translate them into actions due to a lack of money, not having sufficiently strong institutional frameworks or prioritising other developmental activities. The findings indicate that those countries that have a superior mode of governance and access to external sources of financial support are getting ahead with incorporating climate policies in their strategies towards sustainable development. At the same time, bottom-up innovation, localized resilience, and interregional cooperation can be deemed as an effective influencing factor of resilience in vulnerable areas. However, the regions differ as well. Certain nations are very dependent on foreign assistance whereas some nations lack consistency as well as effectiveness in policies. The outcomes indicate the significance of strengthening the capacity of institutions, promoting inclusive policy formulation, and simplifying the process through which people can receive climate funds to bridge the dissimilarity between the policymaking exercises and actual outcomes. This paper suggests that multi-level collaboration, or the combination of local strategies with national planning and international resources, is the key to making climate policy responses in poor countries both fair and effective in reduction of the negative impacts of climate change.
climate policy, developing nations, adaptation strategies, renewable energy, climate finance, sustainable development
Copyright (c) 2024 Noreen Akhtar, Junaid Farooq (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Educational Inequality and Its Impact on Social Mobility
This study investigates the relationship between educational inequality and social mobility through a mixed-method experimental design, integrating quantitative analysis of large-scale data with qualitative insights from lived experiences. The findings reveal that disparities in educational attainment, school completion, standardized test performance, and higher education enrollment are strongly correlated with reduced intergenerational mobility. Quantitative results, summarized in nine detailed tables, highlight persistent gaps across income quintiles, parental education levels, and geographic regions, while twelve figures visualize trends, correlations, and predictive models that confirm the detrimental effects of inequality on upward mobility. Key results indicate that teacher-student ratios, digital access, and resource allocation significantly shape student outcomes, with disadvantaged groups consistently underperforming their advantaged peers. Qualitative evidence further reinforces these patterns by illustrating how structural barriers, limited parental resources, and community-level inequities perpetuate disadvantage across generations. Importantly, regression models demonstrate that educational inequality is a statistically significant predictor of mobility indices, while thematic analyses reveal the mechanisms through which these inequities are transmitted. Collectively, the study confirms that unequal access to quality education entrenches stratification, diminishes opportunity, and undermines the promise of social mobility. The implications underscore the urgent need for systemic reforms that address resource disparities, expand digital infrastructure, and create equitable pathways from early education through higher learning.
Educational inequality, social mobility, intergenerational mobility, digital divide, educational attainment, equity
Copyright (c) 2023 Sadia Munir, Hassan Javed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Parental Involvement and Its Effect on Student Success
This study examined the effect of parental involvement on student success through a mixed-method experimental approach that integrated both quantitative and qualitative analyses. Data from structured parental engagement interventions demonstrated that higher levels of involvement were consistently associated with improvements in student outcomes, including GPA, standardized test performance, attendance, and homework completion. Nine comprehensive tables revealed that parental support positively influenced motivation, behavioral improvements, and participation in extracurricular activities, while twelve figures provided robust visual evidence of longitudinal trends, correlations, and predictive relationships. Notably, line and time-series analyses confirmed steady progression among students with engaged parents, while scatter plots and regression models underscored the predictive strength of parental involvement across contexts. Pie and stacked bar charts further highlighted the proportional and cumulative benefits of academic and motivational support. Thematic insights from qualitative data reinforced the statistical findings, showing that parental communication with teachers, structured at-home guidance, and encouragement were critical drivers of success. The integration of these results demonstrates that both the quality and frequency of parental involvement substantially enhance academic achievement, socioemotional well-being, and holistic development. The study concludes that authentic school–family partnerships are essential for narrowing achievement gaps and promoting equitable educational opportunities, positioning parental involvement as a cornerstone of student success in modern education.
Copyright (c) 2023 Kiran Shehzadi, Yasir Mehmood (Author) https://creativecommons.org/licenses/by-nc-nd/4.0