The rapid integration of artificial intelligence into manufacturing environments fundamentally reshapes worker identity, organizational hierarchies, and labor relations. While technical literature emphasizes efficiency gains from AI-driven automation, critical questions remain about how workers perceive, adapt to, and resist algorithmic management systems. This research examines the sociotechnical dimensions of AI implementation across manufacturing facilities in Iran, South Korea, and the UAE, analyzing how cultural contexts mediate worker responses to automated supervision and predictive maintenance systems.

Through mixed-methods analysis combining worker surveys, organizational ethnography, and machine learning performance data from 847 firms, we reveal significant disparities between technical optimization and social acceptance. Workers in facilities with transparent AI systems reported 43% higher trust levels compared to opaque algorithmic management. Our findings challenge techno-deterministic assumptions, demonstrating that successful AI integration depends less on algorithmic sophistication than on participatory implementation strategies that preserve worker autonomy and dignity.

We introduce a "sociotechnical friction index" measuring resistance points where technological capabilities clash with organizational culture and labor expectations. Results show that facilities prioritizing human-AI collaboration over full automation achieved both higher productivity and lower turnover rates. This research contributes to critical technology studies by documenting how Global South manufacturing contexts negotiate AI adoption differently than Western models assume, offering insights for policymakers addressing technological unemployment, algorithmic accountability, and the future of work in an AI-augmented economy.

In a globalised context where cultural diversity and sustainability are central concerns within the built environment, religious architecture increasingly reflects processes of cultural adaptation and social coexistence. In Bali, mosque architecture offers a distinctive case of acculturation between Islamic architectural principles and a Hindu-majority cultural context. Rather than adopting standardised mosque forms, many mosques in Bali demonstrate adaptive design approaches shaped by local cultural norms and sustainability considerations.

This study adopts a qualitative research design based on secondary data. Data sources include peer reviewed academic literature, architectural drawings, planning and regulatory documents, and publicly available visual records of selected mosques in Bali. A thematic analysis approach is employed to examine how cultural acculturation and sustainability are articulated through architectural form, spatial organisation, and symbolic representation.

The analysis identifies recurring design strategies, including selective localisation of architectural elements, moderated religious symbolism, and contextual spatial adaptation influenced by Hindu Balinese traditions. These strategies demonstrate how mosque architecture responds to cultural context while maintaining religious function and visibility.

The study concludes that mosque architecture in Bali operates as a form of social technology through which Islamic Hindu acculturation contributes to cultural sustainability and social harmony. By framing architecture as a socio-technical practice, this research contributes to social science discussions on Society and Technology and highlights the role of the built environment in sustaining pluralistic and culturally diverse societies.

Introduction: Older adults residing in long-term care facilities often face challenges such as reduced autonomy and limited opportunities for personal growth. While Immersive Virtual Reality (IVR) offers potential for psychological support, evidence regarding its acceptance and feasibility among this population, particularly for those without cognitive impairment, is limited. This study aims to evaluate the feasibility, user engagement, and safety of an IVR intervention designed around Ryff’s Psychological Well-Being dimensions, contrasting active versus passive participation.

Method: An exploratory pilot study was conducted with 12 residents of a long-term care facility (aged 67–95) without cognitive impairment. Participants were assigned to three groups: Active IVR (interactive tasks within WebXR environments), Passive IVR (observational experience of the same environments), and Control. The intervention comprised eight sessions. Assessment included the Ryff Psychological Well-Being Scale (pre-post), the NPT-ES scale (engagement/social interaction), and presence/satisfaction questionnaires.

Results: Although pre–post statistical analysis of the Ryff scale showed no significant changes—consistent with the pilot's exploratory sample size—feasibility indicators were highly positive. Both IVR groups reported high scores in presence and strong engagement (NPT-ES), with participants expressing enjoyment and positive social interaction. Crucially, rejection rates and adverse effects (cybersickness) were negligible, with most participants feeling safe and willing to repeat the experience, regardless of the active or passive modality.

Conclusions: Implementing IVR interventions for older adults in residential care is feasible and safe, generating high satisfaction and positive engagement. While the eight-session pilot did not yield statistical shifts in deep psychological constructs, the high acceptance suggests IVR is a promising tool for social enrichment and meaningful engagement. Future research should scale up the sample size to test clinical efficacy.

Keywords: Virtual Reality; Older Adults; Feasibility; Ryff’s Well-Being; Long-Term Care; Quality of Life.

Introduction
The recent surge in the development of digital labor platforms in India has heightened worries about the issue of income instability and financial insecurity among gig workers. The allocation of tasks, pricing, incentives, and performance assessments are controlled by computerized management systems that tend to bring uncertainty in earnings. At the same time, financial vulnerability is made worse by the lack of access to formal social protection mechanisms. Although earlier studies have addressed the subject of algorithmic control and labor precarity in isolation, there is very limited empirical information that addresses worker perceptions of fairness, income stability, and social protection as a combined factor in income volatility in emerging economies.

Methods
This study used a validated 20-item Likert-scale measure to collect primary data on 220 gig workers on ride-hailing, food delivery, logistics, and home-service platforms in India. Cronbach's alpha (α >.79) was used to assure reliability. A five-factor model with 67.27 percent of overall variance was supported by Exploratory Factor Analysis. Multiple regression analysis was done to discover predictors of income volatility.

Results
The regression model was statistically significant (R² = .419, p < .001). Perceived Income Stability (β = .278, p < .001), Algorithmic Fairness (β = .231, p = .001), and Perceived Social Protection Adequacy (β = .188, p = .005) significantly predicted income volatility. Social Security Awareness was not statistically significant (p = .073).

Conclusions
The conditions of structural platforms and subjective perceptions of fairness, stability, and institutional support play a role in the volatility of incomes in the Indian gig economy, in addition to other factors. To decrease economic precarity within digital labor markets, policy reforms must focus on earnings predictability, algorithmic transparency and sufficient social protection systems.

Social movements are central to Bangladesh’s political and social fabric; scarcely a month passes without one emerging. These movements have repeatedly shaped governance, transforming popular grievances into tangible political and policy outcomes that redefine the nation’s democratic and socio-economic landscape. This study examines the dynamic interplay between public policy and social movements, highlighting how policies can generate public discontent, signal social necessity, and be actively reshaped through citizen mobilization. Drawing on a qualitative, document-based narrative conceptual methodology, the study analyses historical records, news reports, government documents, and scholarly research to explore political and socio-economic mobilizations, encompassing both historical and contemporary episodes. Findings reveal that social movements operate as structurally embedded actors within the governance ecosystem, functioning as informal accountability mechanisms that influence policy content, amplify public scrutiny, and reinforce democratic responsiveness. Policies perceived as unjust, exclusionary, or poorly implemented often serve as triggers for collective action, while weak institutional channels increase the reliance on extra-institutional participation. The study identifies cyclical patterns in which policy decisions, mobilization, and state responses interact recursively, producing adaptive governance outcomes. Moreover, social movements are shown to contribute to broader societal debates, shaping public discourse, highlighting structural inequities, and fostering civic consciousness. The paper concludes with recommendations for participatory policy design, strengthened institutional responsiveness, and the cultivation of formal channels for citizen engagement. It further suggests directions for future research, including longitudinal studies to assess long-term impacts, comparative analyses across national and regional contexts, and the examination of digital mobilization and social media as transformative tools for collective action in contemporary governance. By elucidating the mutually constitutive relationship between policy and social movements, this study contributes to a deeper understanding of Bangladesh’s evolving democratic landscape and the mechanisms through which citizens influence governance outcomes.

Digital platforms have evolved into core infrastructures of contemporary social life; however, their continuous transformation generates persistent forms of collective uncertainty. This paper introduces the concept of platform anxiety to explain how algorithmic environments produce socially shared experiences of instability, unpredictability, and perceived loss of control. Rather than framing anxiety as an individual psychological condition, this study conceptualizes it as a structurally mediated phenomenon emerging from socio-technical design.
Methodologically, the research adopts a qualitative design based on thematic analysis of in-depth user narratives and observed platform interaction practices. The empirical material consists of qualitative data collected from [n = …] active social media users, focusing on their everyday experiences of visibility, algorithmic change, and communicative self-regulation across major digital platforms. Data were analyzed through iterative coding procedures to identify recurring interpretive patterns and adaptive strategies.
The findings indicate that rapid interface changes, opaque algorithmic decision-making, and continuous visibility pressures intensify reflexive self-monitoring and reshape communicative norms. Users respond by developing micro-level risk management strategies, including selective self-disclosure, temporal withdrawal, and identity modulation. These practices significantly influence trust formation, participation patterns, and perceptions of agency within digital environments.
This paper argues that platform anxiety constitutes a defining condition of hyperconnected societies, affecting not only individual well-being but also the structure of digital public interaction. By framing uncertainty as a systemic outcome of platform architecture, this study contributes to interdisciplinary debates in communication theory and digital sociology and offers a robust conceptual framework for analyzing the long-term social consequences of algorithmically mediated communication.

The victimisation of adolescents in digital contexts represents an increasing social and scientific concern. Among the most severe risks is online grooming is a manipulative process through which adults establish deceptive emotional connections with minors to facilitate sexual exploitation (Craven et al., 2006; De Santisteban et al., 2017). Adolescence is a critical period for understanding this phenomenon, as it encompasses psychosocial characteristics such as heightened emotionality, impulsivity, and identity exploration (Salmela-Aro, 2011; Baumgartner et al., 2010), which may amplify exposure to online risks.

Adopting a developmental victimology perspective (Finkelhor, 1995; Piquero, 2015), this study examined how risk factors for online grooming vary across adolescence. Using a quantitative, cross-sectional design, data were collected from 240 adolescents aged 12–19, divided into early-to-mid (12–15) and mid-to-late (16–19) adolescence. Individual (self-esteem, impulsivity, negative emotionality), relational (parental supervision, family relationships), behavioural (risky online behaviours), and prior victimisation factors (cyberbullying) were analysed.

The results identified three main predictors of online grooming victimisation: engagement in risky online behaviours (OR=1.21; SE=0.05; p=<.001), gender (OR=2.49; SE=0.36; p=.012), and previous (cyber)bullying victimisation (OR=2.21; SE=0.32; p=.012). Developmental comparisons revealed that while these predictors were still significant among younger adolescents, only risky behaviours retained predictive power among older participants.

The findings highlight that vulnerability to grooming is developmentally dynamic, shaped by both psychosocial maturation and contextual autonomy. These results underscore the importance of age-specific prevention strategies that promote emotional regulation, digital literacy, and parental mediation to mitigate adolescents’ susceptibility to online grooming.

Background: The principle of the best interests of the child, enshrined in the UN Convention on the Rights of the Child (UNCRC), is a cornerstone of child protection systems. However, translating this principle into everyday practice remains challenging, particularly in contexts with different institutional structures and cultural values. This study builds on research conducted in Lithuania and Latvia during an Erasmus placement, which established partnerships with practitioners and provided direct, context-embedded access to both systems.

Objective: This study examines how social workers in Lithuania and Latvia assess and operationalize the best interests principle in child protection, with a focus on assessment processes, frameworks, and systemic factors that shape child-centered practice.

Methods: This study employed a qualitative, theory-informed design, collecting data through semi-structured interviews with 10 practitioners (micro and macro-level roles) and a document analysis of national legal frameworks and methodological guides. Fieldwork was enabled by the author’s Erasmus-based residency in both countries and was conducted in collaboration with Baltic social work researchers to ensure contextual grounding. Guided by Reflexive Thematic Analysis, Ecological Systems Theory, and the Planned Change process, patterns were identified across micro, meso, exo, and macro layers.

Results: Three themes emerged: (1) Defining and assessing the best interests of the child as a multidimensional, situational process; (2) decision authority and exosystem hierarchies that constrain social workers’ discretion; and (3) persistent policy–practice gaps driven by resource shortages, fragmented coordination, and cultural norms. Comparative analysis revealed Lithuania’s centralized, algorithmic approach promotes uniformity but limits flexibility, while Latvia’s family-centered model prioritizes preservation but relies heavily on Orphans’ Courts.

Conclusions: Assessment in child protection is a practice-in-context phenomenon shaped by systemic structures and cultural attitudes. To make UNCRC Articles 3 and 12 actionable, reforms should institutionalize child participation, strengthen multi-agency coordination, and align decision-making with assessment evidence. Workforce investment and community-level advocacy are critical to narrowing policy–practice gaps.

Artificial intelligence (AI)-enabled systems are increasingly governing access to youth services, yet empirical research remains limited on how young service users experience and evaluate AI-mediated service delivery. Based on procedural justice and institutional trust theory, the present research formulates and pilots a sequential institutional framework between AI-enabled service experience (AISE), algorithmic legitimacy (ALG), trust in AI-supported service systems (TIA), psychological well-being (PWB), and service satisfaction (SS). The respondents included youth service users (N = 418) in Pakistan who stated that they had previously used AI-supported services in education, health, and social welfare or community-based situations. To test the hypothesized relationships, structural equation modeling (SEM) was used and supplemented by importance-performance map analysis to examine the allocation of explanatory influence throughout the sequential model. TIA emerged as the most proximal and influential predictor of both PWB and SS, while ALG operated as a critical upstream mechanism shaping trust. Sequential mediation analyses further show that youth outcomes are influenced less by exposure to AI systems per se and more by evaluative judgments concerning the legitimacy and trustworthiness of AI-supported service processes. By centering youth service users and conceptualizing AI as an institutionalized component of service delivery, this study advances research on algorithmic governance in youth services and offers insights for ethically and accountably deploying AI-assisted systems to support positive youth outcomes.

Introduction

Youth unemployment and the growing number of young people classified as NEET (Not in Employment, Education or Training) represent a major socio-economic challenge worldwide. In countries such as Morocco, this issue is particularly concerning due to persistent difficulties in the transition from education and training systems to the labour market. Although the employability of NEET youth has received increasing scholarly attention, the existing literature remains fragmented and unevenly distributed across research themes and geographical contexts. Consequently, a comprehensive understanding of research trends and gaps is still lacking. This study, therefore, addresses the following research question: What are the main trends, thematic orientations, and geographical gaps in the scientific literature on NEET youth employability and vocational training?

Methods

To answer this question, a bibliometric analysis was conducted using data retrieved from the Scopus database. The search strategy combined the keywords “NEET”, “employability”, and “vocational training”. The dataset was analysed using the Bibliometrix package in R to explore publication trends, influential journals and authors, international collaboration networks, and thematic structures.

Results

The results reveal a significant increase in publications over the past decade, with research primarily conducted in European contexts. Thematic analysis highlights key research areas related to youth labour market integration, skills development, social inclusion, and employment policies.

Conclusion

The study identifies important thematic and geographical gaps, emphasising the need for further research in developing regions such as North Africa.