Digital platforms promise connection, community, and convenience. Yet rising rates of loneliness, declining face-to-face interaction, and increased social fragmentation suggest a paradox at the heart of technological society. This paper argues that contemporary digital economies are structurally incentivized to monetize human isolation rather than reduce it.

Through an analysis of platform design, attention economies, and data-driven engagement models, the study contends that social media and AI-powered systems are optimized to capture attention, prolong screen time, and stimulate emotional dependency. These mechanisms, while profitable, may inadvertently weaken offline social bonds and reshape interpersonal relationships into algorithmically mediated exchanges.

The paper explores how recommendation systems, personalized feeds, and digital consumption patterns contribute to the commodification of intimacy and belonging. It raises a central question: if platforms financially benefit from prolonged engagement, do they have meaningful incentives to foster genuine human connection?

Rather than framing technology as inherently harmful, this research situates the problem within broader political-economic structures that reward engagement over well-being. It concludes by discussing regulatory and ethical frameworks capable of realigning technological innovation with social cohesion.

Ultimately, it asks whether society is confronting a technological crisis or merely adapting to a new economic model built on engineered dependency. If digital platforms thrive when users remain emotionally and socially tethered to their screens, then the boundary between connection and exploitation becomes increasingly blurred. The deeper concern is whether social fragmentation is an unintended consequence of innovation or a predictable outcome of profit-maximizing design.

The rapid expansion of digital transformation has not only reshaped patterns of communication, work, and education, but has also redefined fundamental concepts such as identity, participation, and belonging. This shift has led to the emergence of “digital citizenship” as an extension of traditional citizenship within the virtual sphere. In this context, there is a growing need to develop a coherent theoretical and legal framework for digital human rights that responds to the profound changes technology has introduced into the nature of human existence and interaction. This study aims to analyze the features of a model of digital citizenship that operates across two interconnected realms, the physical and the digital, where individuals exercise their rights and responsibilities within a hybrid environment that merges material reality with cyberspace. The study advances the argument that digital citizenship cannot be reduced to the mere use of technological tools. Rather, it requires recognition of a distinct set of rights reflecting the ontological specificities of digital existence, including the right to internet access, data protection, digital identity, cybersecurity, and freedom of expression on digital platforms. While traditional human rights frameworks remain essential, they are not fully equipped to address the complexities generated by the digital sphere. Furthermore, the analysis demonstrates that effective access to digital human rights is closely linked to prevailing forms of digital inequality, including disparities in technological access, digital literacy, and legal protections. These gaps hinder the realization of digital justice and pose significant challenges to the universality of human rights in the digital age, underscoring the need to rethink public policies to ensure inclusive protection across both physical and virtual domains.

This research explores the evolution of school governance within the European cultural area, building on a theoretical framework established in 2019. Governance is defined here not merely as an administrative act, but as a complex process of decision-making and implementation involving diverse stakeholder networks.

The study utilizes an updated morphological matrix of ideas to analyze the interaction between democratic principles (rights, responsibilities, active participation, and diversity) and key educational fields (value-based education, communication, and discipline). The primary focus is investigating the transition from "hard governance"—characterized by compulsory legal regulations—to "soft governance", which relies on persuasion, shared values, and democratic dialogue.

The methodology employs a robust triangulation approach, collecting data from six distinct categories of actors: school principals, teachers, auxiliary staff, students, parents, and community partners. This multi-level analysis aims to identify the "decisional synergy" required to foster organizational change and development in modern school systems.
Preliminary findings, based on the application of the morphological matrix, suggest that the inversion of the relationship between obligation and assumption of responsibility is key to superior educational quality. The final results will provide a set of indicators for institutional transparency and participatory management, facilitating a more effective dialogue between schools and their communities.

School governance represents a fundamental pillar of organizational development, moving beyond traditional management toward a culture of active democratic participation. This study explores the transition from "hard governance," based on compulsory legal regulations, to "soft governance," which relies on shared values, persuasion, and the perception of internal and external relationships. The research is grounded in the necessity of evaluating how school systems in the European cultural space adapt their decision-making processes to foster systemic change.

In his influential 2016 book Fossil Capital: The Rise of Steam Power and the Roots of Global Warming, Swedish scholar Andreas Malm offered a new explanation for the English cotton manufacturing industry’s transition from rural, abundant, and cheap direct-drive waterpower to urban and more expensive stationary coal-generated steam power. After exonerating waterpower’s unreliability, non-scalability and geographical inflexibility, he argued that the real culprits were capitalists who prioritized controlling their workforce in a time of labor unrest, something more easily achieved in large agglomerations with abundant surplus labor. As such, the current climate crisis is rooted in the outcome of a class struggle rather than inherent advantages of carbon fuels over previous power sources. With adequate public planning and support, moving away from carbon fuels towards preferable alternatives should, therefore, be easier than commonly imagined.

This essay challenges Malm’s historical narrative by revisiting traditional and more recent interpretations with evidence that demonstrates how the combination of costlier steam engines and urban locations delivered greater returns on investment because of factors ranging from reduced transportation costs to easier access to larger and more diverse pools, service providers and skilled labor. A case is made that overturning past outcomes of market processes that factored in numerous trade-offs is much more complex, costly and environmentally damaging than suggested by Malm’s historical narrative.

Introduction:

Artificial intelligence (AI) is slowly entering policing, welfare support, and the legal systems of the Global South, thereby changing how institutions operate. The introduction of AI in the Global South is not only a technological phenomenon of modernization of the equipment, but also a complete restructuring of the government, which was realized by replacing the current infrastructure. Without transparency and challenge mechanisms, the locus of accountability will move not only out of the formal oversight structures, but also into more opaque processes.

Methods:

The research will use a mixed-methods approach to compare the acceptance of AI systems in India, Brazil, and Kenya. It analyzes 35 procurement contracts, AI strategy studies on the national level, and statistical data of predictive policing and welfare automation. Those findings are critically triangulated against 24 semi-structured interviews with judges, public defenders, technologists, and representatives of civil society. In place of gauging the effects on efficiency, the analytical framework focuses on the conversion of operational authority, changes in discretionary space, and the stability of procedural protection within institutional practice.

Results:

It has been found that algorithmic infrastructures mechanize the operational power of proprietary technical ecosystems, thus restricting the discretionary judgment and institutional access to model construction and information logic. Respondents identified a few avenues to challenge automated decisions, noting inconsistencies in regulations. The comparative analysis of the three national settings shows that the tendency to refer to outside vendors and spend minimal internal audit power is universal.

Conclusion:

The introduction of AI in the Global South is not only a technological phenomenon of modernizing equipment, but also a complete restructuring of government, achieved by replacing the current infrastructure. Without transparency and challenge mechanisms, the locus of accountability will move not only out of the formal oversight structures, but also into more opaque processes.

How do predictive monitoring technologies affect the likelihood and form of protest? Classical repression theories analyze state coercion as reactive responses to observable collective action. This framework fails when algorithmic surveillance enables states to intervene before mobilization occurs, inverting the temporal sequence that defines conventional repression. I develop a theory of anticipatory repression wherein states deploy predictive analytics to identify and preempt potential threats rather than responding to manifest challenges. Anticipatory repression operates through three interconnected mechanisms. Perception renders potential dissent informationally visible by capturing behavioral signals through surveillance networks and data scraping. Prediction transforms these signals into probabilistic risk assessments through algorithmic analysis. Preemption operationalizes prediction through early interventions designed to disrupt mobilization before protests become observable in empirical records. These mechanisms generate three testable propositions: predictive surveillance infrastructure deployment (1) reduces protest incidence, with effects strongest for spontaneous, low-threat mobilization; (2) alters protest form by increasing organizational formality and reducing public visibility; and (3) operates similarly across regime types while varying in implementation intensity according to institutional constraints. I employ a nested mixed-methods design combining a quantitative analysis of protest event data with qualitative case studies examining surveillance deployment in China, Nigeria, and the United States. Preliminary analysis suggests that predictive monitoring correlates with reduced mobilization and systematic changes in organizational tactics across different political systems, with significant implications for democratic contestation and civil liberties in an era of ubiquitous surveillance.

This study explores how mother tongue-based multilingual education, strengthened with appropriate educational technology, can advance social and educational empowerment among minority ethnic communities in Bangladesh. It draws on sociolinguistics and the sociology of education to treat language as more than a classroom tool. Language is also a pathway to identity, dignity, participation, and equitable life chances. The research asks how technology-supported instruction affects engagement, attendance, learning achievement, and progression, and how it shapes language attitudes, classroom interaction, and community involvement. A mixed methods design is proposed. Linguistic ethnography will document home and school language practices through classroom observation, interactional transcripts, and interviews with students, parents, teachers, and local leaders. Quantitative measures will track baseline and endline learning outcomes, retention, and teacher practice indicators. The project co-designs and evaluates a low-cost digital support package that works in low-connectivity settings, including offline-first micro-lessons, community-recorded audio stories, bilingual e-books aligned with curriculum goals, and teacher learning modules on inclusive pedagogy and translanguaging. It also examines digital constraints such as device sharing, connectivity gaps, and varied literacy levels so that technology reduces rather than reproduces inequality. The expected contribution is practical evidence for language in education policy, scalable edtech design, and culturally sustaining teaching that can reduce dropout risk, improve foundational learning, and strengthen social inclusion through mother tongue education.

Environmental degradation in Indonesia often affects foothill communities most severely. Deforestation, land conversion, and extractive activities increase the risks of floods, landslides, and the gradual loss of local livelihoods. In Aceh, these problems continue despite the presence of environmental regulations. Weak enforcement and limited monitoring allow activities such as illegal logging and land encroachment to persist. As a result, environmental damage is not only an ecological issue but also a matter of justice, since vulnerable communities bear the consequences of violations that are rarely addressed through effective policing or legal action.

This paper examines forest waqf as a community-based response to these challenges. Waqf is an Islamic endowment in which property or assets are permanently dedicated for public benefit. Once designated as waqf, the asset cannot be sold or transferred and must be used for social or charitable purposes. When applied to forest land, waqf creates a long-term protection mechanism that prevents commercial exploitation and preserves environmental resources for the wider community. The study uses a qualitative case study of forest waqf initiatives in Aceh, drawing on document analysis.

The findings show that forest waqf functions not only as a conservation effort but also as a form of local environmental governance. By placing forest areas under perpetual waqf ownership, communities limit activities such as illegal logging and uncontrolled land conversion, which often occur beyond the reach of formal monitoring. For communities living near forested slopes, these initiatives have practical benefits. Protected forests help maintain water sources, stabilize land, and reduce exposure to environmental hazards. In this sense, forest waqf contributes to environmental protection while also addressing the social impacts of environmental harm. The study argues that forest waqf represents a preventive approach to environmental justice. Instead of relying mainly on policing and punishment, it focuses on long-term stewardship, collective responsibility, and ethical land management.

Algorithms and artificial intelligence (AI) are often portrayed as powerful tools intended to enhance performance and optimize tasks. Yet critical scholarship stresses that these systems operate as socio-technical actors: they are conceived, trained, and deployed within particular institutional and social arrangements, and their outputs may generate distortions in the very domains they are meant to improve. Spatial discrimination—an enduring phenomenon—emerges when resources, opportunities, or services are allocated in ways that sustain or intensify geographic inequalities, sometimes through apparently neutral criteria that nonetheless disadvantage specific places or populations. This study offers a systematic literature review that examines how AI may interact with territorial dynamics and how spatial inequalities can be reproduced through algorithmic decision-making. It identifies two key dimensions through which territorial discrimination can take shape, helping to frame where discriminatory effects may originate and how they may be experienced across space. This paper argues that a critical approach to algorithm implementation is essential to ensure ethical, transparent, and rigorous assessment. Such an approach requires careful scrutiny of underlying assumptions, data sources, proxies for location, and decision rules, as well as attention to governance and accountability in real-world deployments. Overall, this study underscores that AI is not merely a technical instrument but also a force that can reshape spatial governance and influence whether geographical inequality is reinforced or reduced over time.

Abstract

The phenomenon of self-diagnosis regarding mental health disorders has escalated significantly due to the massive influx of educational content aggressively personalized by social media algorithms. The novelty of this study lies in identifying the phenomenon of 'digital identity fusion,' where social media algorithms do more than validate symptoms; they reconstruct mental health labels into instruments for social navigation and self-aesthetics that paradoxically diminish the user’s self-efficacy. This study aims to elucidate how algorithmic mechanisms contribute to reshaping the perception of mental illness, shifting the paradigm from a clinical diagnosis to a central facet of the user’s self-identity. Methods: Employing a qualitative phenomenological approach (Interpretative Phenomenological Analysis), this research involved three participants (n = 3) selected through purposive sampling to represent different social pressure spectrums: a university student, a private employee, and a creative freelancer. Primary data were collected through in-depth interviews focusing on the history of algorithmic exposure and the motivations behind self-diagnostic behavior. Results: The results indicate that algorithms create echo chambers that trigger confirmation bias, leading individuals to adopt labels such as ADHD or Anxiety as self-defense mechanisms against external pressures. The findings reveal an identity fusion in which mental health labels are used as aesthetics or personal branding to construct a unique or "authentic" self-narrative within digital spaces. Collectively, these interactions with algorithms have diminished participants' self-efficacy, as individuals feel bound to a permanent "disease identity". Conclusion: The study concludes that self-diagnosis has shifted from a mere search for medical information toward the formation of a core identity used for social navigation. Consequently, future psychological interventions must integrate algorithmic literacy to restore individual personal agency.