Search Results (87)

Cariño (care) should be central to equity-centered transformation in science, technology, engineering, and mathematics (STEM) higher education. Yet, relational leadership practices that prioritize culturally grounded care—such as cariño—are often absent in STEM initiatives, leaving unexamined how Women of Color (WOC) enact these practices to advance equity for historically marginalized students. Employing a qualitative methodology grounded in Chicana Feminist Epistemology, in-depth interviews were conducted with five WOC leading a multi-institutional, federally funded STEM initiative. Analysis revealed four interrelated dimensions of what we are calling “Cariño Competence”: (1) relational attunement grounded in moral obligation, (2) protective action when project systems fail students, (3) boundary-setting as care and resistance to extractive labor, and (4) community-sustained resilience through networks of WOC leaders. The findings offer a data-driven theorization of Cariño Competence, capturing how WOC operationalize culturally grounded care as a strategic, protective, and resistive praxis. By centering students as the moral and epistemic anchor of leadership decisions, this study demonstrates how relational, culturally sustaining practices can humanize bureaucratic systems, buffer harm, and advance systemic transformation in STEM higher education. These insights contribute to scholarship on culturally responsive leadership and provide a practical framework for advancing equity, inclusion, and empowerment in higher education contexts. Full article

Notwithstanding the cruciality of the decolonisation project in decentring African perspectives and experiences in education, very few studies have explored the extent to which the Fallist Movements in South Africa have presented foundational pathways for academic staff to negate colonial legacies and recentre African thought systems. Through a systematic literature review of research from the public domain, this study couched within the decolonial lens explored university students’ concerns, embedded in the Fallist Movements in South Africa, and how academic staff could draw lessons from student actions to decolonise education. After screening the initial 65 entries, based on the exclusion and inclusion criteria, 19 research studies published between 2015 and 2025 were retained for analysis. Findings reveal three recurring concerns: disrupting positionality in colonial categories of universities, reasserting their Being, and agitating for a decolonised curriculum, of which these embodied the spirit of students’ resilience against cultural colonisation, epistemic erasure, and economic exclusion. Building on these findings, the paper argues that such resilience from students enlightens the strategies academic staff could learn to transform the decolonisation project into reality. Implications for the academic community in South Africa and comparable contexts are proposed to resuscitate the unfinished business of decolonising education. Full article

This article presents a structured literature review of remittances, migration and economic policymaking in countries of origin, with a focus on Kenya, Kerala (India), and Sri Lanka. It examines three linked bodies of scholarship: migration as a driver of economic growth, the political economy of migration policymaking, and evidence-informed policymaking (EIPM). Conducted with a scoping orientation, the review focuses on contemporary academic and policy literature published since 2000 and shows that the evidence base on the economic value of international remittances in the context of labour migration is extensive, including findings on poverty reduction, macroeconomic stability, financial inclusion and diaspora engagement. However, this evidence is unevenly integrated into policymaking. The review finds that under-utilisation is not simply a problem of insufficient data or weak analytical capacity. Rather, it reflects structural, political and epistemic dynamics that shape how evidence is produced, legitimised, filtered and used in origin-country settings. It further shows that destination-centred perspectives continue to dominate migration scholarship, while gender and digitalisation are best understood as cross-cutting features of evidence systems rather than peripheral themes. The article concludes that strengthening the developmental contribution of migration and remittances requires greater attention to the institutional and political conditions under which economic evidence becomes policy-relevant and actionable. Full article

Driven by China’s “dual carbon” (carbon peak and carbon neutrality) goals and the national strategy of new-type urbanization, prefabricated construction has emerged as a pivotal pathway toward industrialized and sustainable development in the construction sector—leveraging its distinctive advantages in construction efficiency, cost optimization, environmental performance, and design adaptability. Nevertheless, the inherently sequential and interdependent nature of the full construction process—encompassing off-site component manufacturing, logistics transportation, and on-site assembly—introduces pronounced cross-stage risk transmission mechanisms, with prefabricated components serving as critical risk carriers. Such transmission dynamics significantly impede the scalable and safe deployment of prefabricated construction. To date, scholarly efforts on construction safety in prefabricated buildings have predominantly addressed isolated, stage-specific risks, falling short in quantitatively modeling the coupled propagation of risks across stages, accommodating epistemic uncertainties and latent (i.e., unknown or unobserved) risks, and informing targeted, evidence-based mitigation strategies. To bridge this gap, this study develops a rigorous quantitative framework for assessing cross-stage risk transmission in prefabricated construction safety. Specifically, it aims to (i) uncover the structural patterns and driving mechanisms underlying inter-stage risk propagation; (ii) reduce the likelihood of safety incidents throughout the construction life cycle; and (iii) deliver actionable theoretical insights and methodological guidance for practitioners and policymakers. Methodologically, we first conduct a systematic identification of safety-critical risk factors and establish a hierarchical risk indicator system comprising three first-level dimensions and twenty second-level indicators. Second, using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, causal relationships among risk factors are clarified, while incorporating the Leaky Noisy-or Gate (LNOG) extended model to account for unknown risks. Risk data are processed using triangular fuzzy functions, and a Bayesian network (BN) topology diagram is constructed via the GeNIe 5.0 platform, forming a DEMATEL-LNOG-BN-based model for assessing cross-phase risk transmission. Finally, applying the model to an actual project—”a prefabricated construction project in Shanghai”—the study conducts a cross-phase risk transmission analysis. Through forward probability inference, backward causality tracing, sensitivity analysis, and pathway decomposition, sensitivity comparisons are performed under different LNOG unknown risk parameters. Results are compared with those from the traditional DEMATEL-BN model to validate the stability and consistency of high-sensitivity risk factor identification, comprehensively verifying the applicability and predictive reliability of the proposed DEMATEL-LNOG-BN model. The study quantitatively reveals the progressive diffusion and amplification mechanisms of risks across the production–transportation–assembly process, providing scientific support and practical reference for precise safety risk prevention, critical node control, and the optimization of management systems in prefabricated construction sites. Full article

Suicide is commonly approached through clinical and psychological frameworks centred on the individual, alongside social explanations emphasising collective conditions. These perspectives offer complementary leverage for understanding and preventing suicidal behaviour. Between these levels, a clinically decisive segment can be specified with greater precision for psychiatric practice, namely the processes through which suffering becomes speakable, socially legitimate and clinically actionable, or is displaced into self-censorship, isolation and delayed help-seeking. This paper advances a service-facing biosemiotic model of suicide risk that formalises this segment as a communicative infrastructure and links it to the public circulation of suicide narratives across media and digital environments. The model comprises two coupled modules. The first, the communicative-classification module, characterises labelling and delegitimation operations that allocate epistemic credibility to crisis talk, foster self-stigma and increase the social cost of disclosing suffering. The second, the public-feedback module, specifies how media representation and repetition regulate the symbolic availability of narrative scripts, with closure- and openness-oriented configurations positioned along the Werther–Papageno continuum. Coupling the modules yields testable propositions concerning mediation via anticipated sanction and moderation by stigma and speakability and identifies conditions under which protective content may show limited translation into help-seeking behaviour. Implications are outlined for how the model may inform therapeutic risk assessment, continuity of care, and prevention. These implications are framed as hypotheses and implementation-relevant considerations derived from the model, with emphasis on (i) operationalising speakability as a clinically evaluable dimension, (ii) identifying institutional conditions that may reduce the communicative cost of help-seeking, and (iii) aligning public communication strategies with international reporting standards. The model is intended to support future empirical testing rather than to establish effectiveness at this stage. Full article

The growing interest in visual methodologies within the educational field reflects the need to rethink teaching–learning processes from a participatory, multimodal, and inclusive perspective. Among these approaches, PhotoVoice emerges as a research–action and training strategy that combines photography and autobiographical narration, activating accessible expressive practices centred on subjectivity and lived experience. This contribution presents a theoretical–methodological analysis grounded in pedagogical and visual research literature, aiming to outline an operational framework for the educational application of PhotoVoice in inclusive pathways addressed to individuals with intellectual disabilities. Framed within the paradigm of Visual Education and a pedagogy oriented toward recognition and relationality, PhotoVoice is examined as a pedagogical device capable of fostering symbolic mediation, identity construction, and narrative agency. The photographic image, conceived as an embodied, situated, and relational language, enables access to forms of knowledge often excluded from dominant verbal codes, restoring visibility and epistemic dignity to marginalised subjectivities. The paper delineates key operational phases of the method and identifies core educational objectives, including the strengthening of narrative agency, self-determination, and reflective participation. From this perspective, visual narration is configured as a situated pedagogical practice integrating aesthetics, ethics, and social transformation, capable of generating equitable and meaning-generative learning environments. Within this framework, PhotoVoice shifts inclusion from an abstract principle to a concrete educational process, enabling participants to narrate, interpret, and actively reshape their own learning contexts. Full article

Artificial intelligence (AI) systems increasingly mediate how individuals learn, work and make decisions, raising foundational philosophical questions about the nature of knowledge, agency and autonomy. This article integrates philosophical analysis with illustrative empirical cases from Romania to examine how AI restructures human epistemic and practical activity. A central empirical observation, the engagement–performance paradox, reveals that AI-driven learning environments can produce dramatic increases in learner interaction while generating only marginal improvements in understanding. Interpreted through post-phenomenology, virtue epistemology and theories of autonomy, this paradox highlights the emergence of epistemic superficiality: a condition in which algorithmically mediated engagement replaces reflective, conceptually grounded learning. Complementary findings from AI-supported workplace contexts further illustrate how intelligent systems automate aspects of decision-making, thereby reshaping autonomy, responsibility and the phenomenology of action. Synthesizing these insights, the article argues that AI functions as a structuring force that co-authors human agency by reorganizing the conditions under which cognition and action occur. The study contributes to contemporary debates in the philosophy of technology, epistemology and AI ethics by proposing the concept of structured agency as a lens for understanding how AI-mediated environments transform the foundations of knowledge, autonomy and human flourishing. Full article

Prosignification is defined as the process through which the subject generates new meanings by engaging in aesthetic experience, critical reflection, and creative action. Unlike general theories of meaning-making, which primarily describe the cognitive organization of experience, prosignification foregrounds the symbolic–expressive dimension as the central site of meaning production. It refers to the individual and collective capacity to construct meaning from expressive and symbolic experiences, integrating cognitive, emotional, social, and cultural dimensions of learning through intentional creative mediation. Prosignification operates between knowledge construction and subjective experience, enabling learners to connect conceptual understanding with personal interpretation and emotional involvement. Whereas knowledge construction emphasizes epistemic development and transformative learning focuses on perspective transformation through critical reflection, prosignification centers on the aesthetic reconfiguration of experience through symbolic creation and interpretation. Rooted in constructivist and experiential approaches, it unfolds through active, student-centred methodologies, particularly in Project-Based Learning contexts. However, its distinctive contribution may lie in integrating reflection, expression, and creation as interdependent mechanisms of meaning generation. Art education constitutes a particularly relevant context for this process, as its symbolic nature fosters the embodied and shared construction of meaning. Thus, prosignification cannot be reduced to cognitive restructuring or attitudinal change but involves the expressive re-symbolization of lived experience. Full article

Transdisciplinary Research (TDR) leverages shared concepts to foster mutual learning among diverse stakeholders, relying on “boundary objects” to shape collective identities and visions. However, the existing literature often overlooks the critical roles of subjectivity and conflict in this process. This paper introduces an analytical framework to examine the construction of these objects, using the “Oasis Project” in the Ecuadorian Andes as a central case study. A research-action project on pesticide-free territories in Ecuador unearthed a question during its implementation on how to achieve collective action when key actors are in conflict with each other. Using TDR to find boundary objects where different viewpoints can find shared meaning, it was determined that there is not enough conceptual clarity in the literature around how conflict can actually help achieve coordination. Using a variety of qualitative methods, such as interviews, participatory observation, and analysis of WhatsApp group message texts, this study shows how the novel concepts of boundary entanglements and conflicts can help other researchers and practitioners facilitate impactful TDR. This study emphasizes three transformative lessons for sustainability science: first, boundary objects are inherently dynamic, evolving through continuous social negotiation rather than static definition; second, their successful consolidation requires deep integration into local knowledge systems, cultural norms, and governance structures; and third, and perhaps most critically, conflict and operational breakdowns are not indicators of failure; rather, they serve as vital diagnostic tools that unveil hidden power relations and epistemic boundaries, providing essential moments for critical reflection and the recalibration of collaborative sustainability strategies. Full article

Local and Indigenous knowledge (LIK) systems are recognised as a pertinent component of effective and equitable water governance, especially for building resilient, sustainable, and climate-resilient water management systems; however, their incorporation into water governance systems and processes remains limited, symbolic, and hindered by technocratic, legal, and power barriers. This study, through a systematic overview of existing work from Africa, aims to explore critically the role and contribution of LIK systems in water governance and climate adaptation, with the goal of establishing that LIK systems should be understood and operationalised as a water governance system, not as a supplementary knowledge system. Through systematic thematic analysis, four recurring themes are identified: (i) rhetorical recognition of LIK without substantive institutionalisation; (ii) evidence of contributions to local-scale climate adaptation, ecosystem management, and water resource allocation; (iii) inherent challenges of legal marginalisation, epistemic dominance, and power asymmetry; and (iv) transformative limitations of participatory or co-management frameworks that maintain state-led authority. SWOT analysis reveals LIK’s strengths in adaptive innovation, knowledge coproduction, and governance legitimacy, with potential threats of marginalisation, institutional fragmentation, and dominance by technocratic discourses. The results show that the failure of integration is governance-driven rather than knowledge-driven, emphasising the importance of institutional recognition, legal pluralism, vertical integration, and the sharing of power. Partnership with LIK as an equal in governance helps create policy environments that are inclusive, flexible, and socially legitimate. This approach to integration directly contributes to the achievement of SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), SDG 10 (Reduced Inequalities), SDG 16 (Peace, Justice, and Strong Institutions), and SDG 17 (Partnerships for the Goals). This review establishes a conceptual, empirical, and practical basis for incorporating LIK into water governance, promoting adaptive, equitable, and resilient water resource management in a climate of uncertainty and complexity. Additionally, the review argues that climate-resilient water governance requires institutional recognition of legal pluralism, vertically integrated decision-making structures, and explicit power-sharing arrangements that treat LIK as coequal governance rather than consultative input. By reframing LIK integration as a question of authority and institutional design, this review contributes to debates on epistemic justice and adaptive water governance under climate change. While grounded in African case studies, the findings contribute to broader global debates on epistemic pluralism and inclusive water governance. Full article

Multi-agent perception systems must operate under fundamental asymmetries: some agents provide fast but unreliable observations, while others deliver higher-quality evidence with delay and uncertain correspondence. Traditional deterministic orchestration and rule-based fusion struggle to manage these trade-offs, often producing brittle or unstable behavior. We introduce a probabilistic orchestration framework that treats coordination as an epistemic generation problem—constructing and updating belief states under uncertainty—rather than a selection problem. Instead of committing to a single agent’s output, the orchestrator constructs a belief state that explicitly represents uncertainty, evidential provenance, and temporal relevance. Decisions are produced through latency-aware, association-weighted fusion, and uncertainty itself becomes a first-class signal governing action, deferral, and learning. Crucially, the orchestrator enables controlled teacher–student adaptation: high-confidence, well-associated stationary observations are gated into a feedback loop that improves ego perception over time while mitigating error amplification. We demonstrate the approach on an infrastructure-assisted dual-camera obstacle-recognition task. Experimental results show improved robustness to distance, occlusion, and delayed evidence compared to ego-only and deterministic orchestration baselines. By operationalizing orchestration as epistemic generation, this work provides a unifying framework for robust decision-making and safe adaptation in multi-agent systems, with implications that extend beyond perception to agentic and generative AI architectures. Full article

Background/Objectives: Psilocybin has re-emerged as a promising intervention for neuropsychiatric disorders including major depressive disorder, treatment-resistant depression, anxiety associated with life-threatening illness, obsessive compulsive disorder, and substance use disorders. However, conventional randomized controlled trials (RCTs)—the current gold standard in evidence-based medicine—may not adequately capture the therapeutic complexity of psilocybin, which depends not only on pharmacological action but also on contextual, psychological, and interpersonal factors. This critical narrative review aimed to evaluate the adequacy of existing clinical research frameworks for assessing psilocybin’s therapeutic potential and to explore alternative methodologies that may better reflect real-world clinical conditions. Methods: Using the Web of Science Core Collection database, we identified and analysed the ten most cited clinical studies on psilocybin published between 2015 and 2025 inclusive. Additional literature was included through reference cross-checking, systematic reviews, meta-analyses, and interdisciplinary sources covering neurobiology, history, and real-world evidence (RWE). The review synthesizes clinical outcomes, methodological constraints, and epistemic considerations relevant to psychedelic-assisted therapy. Results: Evidence from highly cited trials demonstrates rapid and sustained antidepressant and anxiolytic effects of psilocybin, with notable benefits also observed in addiction treatment. However, significant methodological limitations were identified, including selection bias, challenges in placebo design and blinding, small sample sizes, and the underrepresentation of diverse populations. Psilocybin outcomes were strongly influenced by subjective experience and contextual factors such as set and setting. Emerging RWE studies revealed heterogeneous patterns of response and provided insights unattainable through RCTs alone. Conclusions: Psilocybin shows considerable therapeutic promise, but current RCT methodologies capture only part of its clinical effects. Comprehensive evaluation will require larger and more diverse clinical trials, long-term follow-up, standardized psychotherapeutic protocols, and the integration of RWE to reflect real-world practice. Psychedelic-assisted therapy should be conceptualized as a complex intervention that combines pharmacological and psychotherapeutic components. Full article

We propose Adaptive Inference, a portfolio management framework extending Active Inference to non-stationary financial environments. The framework integrates inference, control, and execution under endogenous uncertainty, modeling investment decisions as coupled dynamics of belief updating, preference encoding, and action selection rather than optimization over fixed objectives. In this approach, portfolio behavior is governed by the expected free energy (EFE) minimization, showing that classical valuation models emerge as limiting cases when epistemic components vanish. Using train–test evaluation on the ARKK Innovation ETF (2015–2025), we identify a Passivity Paradox: frozen belief transfer outperforms naive adaptive learning. A Professional Agent achieves a Sharpe ratio of 0.39 while its adaptive counterpart degrades to $-0.28$, reflecting belief contamination when learning from policy-dependent signals. Crucially, the architecture is not designed to generate alpha but to perform endogenous risk management that mitigates overtrading under regime ambiguity and distributional shift. Adaptive Inference Agents maintain long exposure most of the time while tactically reducing positions during high-entropy periods, implementing uncertainty-aware passive investing. All agents reduce realized volatility relative to ARKK Buy-and-Hold (43.0% annualized). Cross-asset validation on the S&P 500 ETF (SPY) shows that inference-guided risk shaping achieves a positive Entropic Sharpe Ratio (ESR), defined as excess return per unit of informational work, thereby quantifying the economic value of information under thermodynamic constraints on inference. Full article

This research introduces a novel approach for seismic fragility assessment by employing a long short-term memory (LSTM) neural network to identify the most effective scalar and vector intensity measures (IMs). This approach enables the rapid and accurate plotting of vector fragility surfaces for shield tunnels embedded in layered soils and subjected to seismic actions. First, an extensive suite of two-dimensional, fully nonlinear soil–structure interaction analyses was executed to generate ground–motion–structure response pairs. These records were subsequently leveraged to train the LSTM network, which received free-field acceleration time histories and directly output critical engineering demand parameters along the tunnel lining. The developed framework significantly mitigates computational expenses while maintaining an acceptable level of fidelity relative to the reference finite element results. Consequently, it serves as an alternative to traditional time history evaluation techniques. Second, we conducted an IM screening process using the results of the LSTM predictions. On the basis of criteria such as relevance, efficiency, practicality, and professionalism, we benchmarked 17 scalar IM and 3 vector IM candidate schemes. The findings indicate that the peak ground velocity (PGV) serves as the most effective scalar IM, whereas the combination of peak ground acceleration (PGA) and PGV forms the optimal vector IM. Finally, probabilistic demand and capacity models are integrated within a fully analytical fragility formulation to derive both scalar and vector fragility estimates. Comparative evaluation reveals that vector IM based fragility surfaces markedly reduce epistemic uncertainty and furnish refined probabilistic descriptions of damage states (DSs) across the seismic demand space. Full article

The critical buckling load factor λ_cr is routinely used as predesign indicator for natural-draft cooling towers, yet its safety meaning is often opaque because imperfection sensitivity and modelling options are embedded implicitly. In this study, λ_cr is formalised as a product of partial contributions within a screening-level predesign framework—?not a normative limit-state format—and the contributions associated with geometric imperfections and FE discretization are calibrated explicitly. Eigenvalue analyses on representative tower geometries under combined self-weight and wind actions are complemented by imperfection-sensitivity curves and a systematic mesh/element-type study. The numerical implementation is additionally verified against published benchmark towers to provide a traceable reference before the parametric analyses. The results show that admissible modelling options can produce non-negligible scatter in λ_cr, while realistic geometric imperfections lead to a comparatively stable range. By separating actions, material, brittle failure, imperfection and discretization contributions, λ_cr can be interpreted consistently as a predesign global stability factor of the order of four for typical cooling-tower configurations, with the discretization-related term interpreted as a framework-dependent epistemic contribution, providing a transparent bridge between linear indicators and nonlinear verification. Full article