Social Sciences

Abstract: Participatory systems have been widely adopted in citizen science, environmental monitoring, urban governance, and public collaborative decision-making. Traditional usability theory focuses on individual task performance and user satisfaction, which cannot adequately explain or support voluntary collective participation, participant recruitment, and long-term engagement. To address this gap, this study introduces the new concept participatability and develops a dedicated assessment framework for participatory systems. Based on a systematic review of usability criteria and the unique socio-technical features of participatory systems, this study defines five core evaluation dimensions: salience, adaptability, congruence, privacy safeguarding, and interactive engagement. Two complementary case studies, including a mature citizen science platform and a newly developed campus participatory planning system, are conducted to validate the framework. Empirical results show that participatability is significantly associated with user acceptance, participation willingness, data contribution quality, and long-term system sustainability. Users in collective participation scenarios prioritize participatability over conventional usability. This study provides a theoretically sound and practically applicable framework for understanding, evaluating, and designing participatory systems. The proposed concept and criteria address critical limitations of existing theories and offer practical guidance for system developers and practitioners to improve participation effectiveness.

Abstract: Purpose: This paper explores why evidence-based policies that appear effective in one context frequently produce uneven outcomes, exclusion, or legitimacy challenges when transferred across policy and governance contexts. It introduces the Contextual Research Validity Index (CRVI) as a diagnostic framework for evaluating whether the contextual conditions necessary for policy validity remain aligned across settings. Methodology: The study develops a conceptual and diagnostic framework that assesses contextual validity across four dimensions: epistemic alignment, institutional fit, cultural resonance, and operational feasibility. The framework is illustrated through an interpretive analysis of India’s Aadhaar digital identification system, drawing on secondary literature, policy reports, and institutional evidence. Limitation: The paper is conceptual and illustrative rather than predictive or causal. The CRVI scoring approach is heuristic and based on qualitative interpretation rather than statistical modelling or original empirical data collection. Findings: The analysis demonstrates that policy effectiveness cannot be separated from contextual conditions. The Aadhaar case shows that interventions regarded as technically successful may still generate exclusion, legitimacy disputes, and uneven outcomes when epistemic assumptions, institutional safeguards, cultural expectations, and operational realities are misaligned. Practical Implications: The CRVI provides policymakers and evaluators with a structured tool for assessing transfer readiness, contextual risk, and governance vulnerabilities before scaling or replicating interventions across settings. Social Implications: The framework supports more accountable and context-sensitive policymaking by helping reduce exclusion, governance failures, and legitimacy erosion in large-scale policy interventions, particularly in digital public infrastructure. Originality: The paper contributes to the policy evaluation and governance literature by reframing policy failure as a problem of contextual misalignment rather than of insufficient evidence alone, and by operationalising contextual validity through a transferable diagnostic framework.

Abstract: This paper explored how Individual personality traits influence student’s acceptance and response to the various digital learning systems. In addition it identified the benefit and potential risks of integrating AI system to personalized learning. AI systems in higher education can integrate personality factors to enhance student engagement and learning outcomes. Instructional approach based on personality traits can improve learning experiences by adapting AI tools. AI tools that recognize students difference for example in terms of pace, interaction style, and type of emotional support can hasten effective and creative learning environment. To strength participation within the academic community; the advantages of personality-driven adaptive learning must be carefully balanced with ethical and human-centered implementation. The misuse of these tools can lead to privacy violations, bias, or stereotyping. However implementing proactive ethical and pedagogical safeguards are crucial to reduce these potential risks. In addition, it is significant to ensure that such AI supports are not replaces human educators. Instead it complements human teaching by promoting self-regulation, well-being, and community belonging.

Abstract: The rapid advancement of digital technologies has fundamentally transformed the operational landscape of higher education institutions globally. This article examines the theoretical and practical dimensions of digital strategy formation within universities and other higher education establishments, with particular emphasis on the strategic management mechanisms that underpin effective digital transformation. Drawing on contemporary frameworks of strategic management in education and insights derived from international practice, the study synthesizes existing knowledge on how higher education institutions conceptualize, develop, and implement digital strategies to enhance educational quality, organizational performance, and institutional competitiveness. The paper explores the core functions and directions of digital strategy, including technology-enabled governance, curriculum innovation, data-driven decision-making, and digital infrastructure development. Special attention is devoted to the alignment between strategic planning processes and digital management systems, highlighting how institutions can leverage structured planning methodologies to navigate the complexities of digital change. The analysis integrates perspectives from strategic management theory and applies them to the educational context, illustrating how administrative leadership, faculty engagement, and stakeholder collaboration contribute to successful digital strategy execution. Furthermore, the article identifies critical success factors and recurring challenges encountered during digital transformation, offering actionable recommendations for institutional leaders and policymakers. The findings suggest that sustainable digital transformation in higher education requires a coherent, institution-wide strategic framework that integrates technological, human, and organizational resources. The article contributes to the growing body of literature on digital governance in education by providing a comprehensive conceptual analysis grounded in recent empirical and theoretical scholarship.

Abstract: YouTube has become a significant but largely unstudied forum for public intellectual two-way conversations on AI in education as video has become a ubiquitous medium for communicating ideas. In a world dominated by video as a communication medium, YouTube has become a prominent location for two-way ideas exchanges about artificial intelligence (AI) in education that is not yet well studied as a site of discursive production. These conversations have the potential to influence and shape access to AI in education on an even larger scale than the scholarly publications they would enable, and these influences are evident in the policy, practice, and teacher identity for which these images of the future of education are constructed. The three-dimensional Critical Discourse Analysis (CDA) model by Fairclough (1992, 2003) is applied to a Corpus consisting of 20 (171,676 words) high-reach and purposively selected panel discussions (8) on YouTube from 2020 to 2026 with Nobel Prize winners, panelists of the WEF, researchers at the Stanford Human-Centered AI Institute and panelists of the UNESCO chair. The six dominant discourse themes found through a process of analysis across 26 deductive and inductive codes, managed by NVivo 15, the student’s were: the discourse of inevitability, the teacher identity crisis, ethics in-depth arising from the question of governance, the equity paradox, the human exceptionalism, and the corporate authority. The results indicate that these themes support the educational future of AI in three systematic discursive processes: inevitability normalization, institutional authority concentration and equity instrumentalization. The findings recognize that the lack of practitioner educators outlined in each of 20 panels is in itself a form of discursive power, as absence rather than content. The study is intended to demonstrate that talking about AI in education is not only a reflection of educational futures, it is an act to creating them. As educators, policymakers, or communities aim to understand and embrace AI adoption as a democratic process, it is crucial that their discursive mechanisms are made visible. Recommendations are made for policy makers, schools, teacher educators, curriculum planners and researchers.

Abstract: Social anxiety (SA) negatively impacts myriad aspects of an individual’s life. Although research with adults and children highlights an important link between SA and social-cognitive abilities (e.g., reasoning about others’ thoughts and emotions), findings are mixed. We hypothesized that these mixed findings stem from the various combinations of social-cognitive components of SA under investigation and the different types of measures used. Understanding these relationships in middle to late childhood is especially important, given that it is a period of substantial social-cognitive development and a common onset age for SA. Seventy-eight children (Mage=8.15 years, SD=1.61) and their parents completed measures capturing different components of anxiety (i.e., social worry, fear of negative evaluation, and social avoidance) and social cognition (i.e. emotion recognition, mental state understanding, and social perspective taking). Contrary to our expectations, measures of social cognition were only weakly correlated. Consistent with our expectations, associations between social cognition and social anxiety were measure-dependent. Self-reported fear of negative evaluation emerged as a positive predictor of accuracy in a behavioral measure of mental state understanding but a negative predictor of parent-reported mental state understanding. In addition, social avoidance accounted for additional variance only when predicting lower self-reported perspective-taking. Together, our findings underscore the multifaceted nature of social cognition and SA and highlight the need for distinguishing these facets in future work.

Abstract: Remote viewing, also called anomalous cognition in much of the laboratory literature, has generated a substantial but controversial body offree-response experiments, operational reports, and theoretical interpretations. Yet the field still lacks a viable source–receiver mechanism that can explain how target-correlated information could arise, how it could be transduced by the body, and why successful reports often appear as fragments, sketches, shapes, textures, gestalts, and nonanalytic impressions rather than as literal transmitted pictures. This paper proposes a conditional source–receiver hypothesis. The target is modeled not as a semantic transmitter but as a structured physical system whose geometry, entropy gradients, chirality, motion, temporal modulation, and boundary conditions may shape a weak source-correlatedperturbation. The receiver is modeled as an active biological system in which weak spin-dependent or connection-like perturbations could bias phase-sensitive biochemical processes, especially radical-pair singlet–triplet dynamics in chiral hydrated molecular environments. Redox feedback, chromatin and hydration dynamics, and larger body/brain state variables could then amplify microscopic phase biases into changes of embodied state. Conscious report is treated as a template-resonance output: the receiver reconstructs weak state shifts through learned geometric, somatic, symbolic, and perceptual templates. The framework is not offered as proof of remote viewing, nor as a claim that torsion or any particular exotic field has been established. Rather, it is a testable architecture that motivates three experimental paradigms to try and bring a clearer picture: Fourier-holographic target tests, geometric-masker tests, and dot/dash numerical-carrier tests. It also motivates retrospective corpus analyses of archived remote-viewing sessions for entropy direction, local ordering, drawing morphology, and geometric primitives that were not always emphasized in earlier scoring systems.

Abstract: The factor structure of the Utrecht Work Engagement Scale (UWES) has been debated, with studies alternately supporting unidimensional and three‑factor solutions. This inconsistency may reflect a methodological limitation: conventional confirmatory factor analysis (CFA) cannot always separate general from dimension‑specific variance, producing similar fit indices across competing models when a dominant general factor is present. We examined the dimensionality of the UWES‑17 and UWES‑9 in a sample of 755 Chilean university students, comparing unidimensional, three‑factor, second‑order, and bifactor models using Weighted Least Squares Mean and Variance Adjusted (WLSMV) estimation appropriate for ordinal data. Bifactor indices, explained common variance (ECV), percent of uncontaminated correlations (PUC), and hierarchical omega (ωₕ), were computed to evaluate essential unidimensionality. Results indicated that a general engagement factor explained approximately 85% of common item variance in both versions (ECV ≈ .85; ωₕ > .90), while specific factors for vigor, dedication, and absorption retained negligible reliable variance, particularly absorption (ωₕ ≈ .00). Measurement invariance by sex was supported for the UWES‑9 at the metric level. Taken together, findings suggest that the apparent multidimensionality of the UWES may be, at least partly, an artifact of conventional CFA modeling rather than a substantive property of the construct in this student sample. For applied monitoring of student well‑being, the UWES‑9 total score is recommended as the most pragmatic and psychometrically defensible scoring approach. Implications for interpreting prior literature and for institutional and educational practice are discussed.

Abstract: Background/Objectives: Iraq's the rate of neonatal is still high amid international efforts to improve child survival. Reversing the trend is determined by caregivers' ability to spot newborn danger signs (NDSs) early on, concentrating on the "first delay" in the care-seeking procedure. The objectives of this research were to evaluate parents' basic understanding of NDSs in Al-Hilla, Iraq, and identify the particular sociodemographic variables that impact these awareness levels. Methods: We performed a multicenter, cross-sectional study at seven primary care centers. Our sample included 383 parents of babies (ages 0–12 months), selected sequentially. Data were collected by structured in-person interviews using the validated Arabic Questionnaire for Neonatal Danger Signs (AQ-KNDS). Knowledge was evaluated on a scale of 0 to 28 and classified as poor, moderate, or good. Binary logistic regression with SPSS v.26 identified significant characteristics associated with high-level knowledge (p < 0.05). Results: The survey found that 73.6% of respondents had "good" knowledge, with a mean of 23.31 ± 3.71. Important clinical gaps were noted: only 22.2% correctly recognized the absence of an anal opening as a surgical crisis and 36.6% correctly identified the startle reflex as a normal biological response, despite nearly everyone (99.2%) recognizing acute symptoms such as fever and difficulty breathing. Prior neonatal risk training (AOR = 2.85, 95% CI: 1.18–6.87, p = 0.020), maternal gender (AOR = 2.81, 95% CI: 1.54–5.10, p = 0.001), and a history of hospital admission for a child (AOR = 2.00, 95% CI: 1.18–3.39, p = 0.010) were the strongest independent predictors of adequate knowledge. Conclusions: In Al-Hilla, parental awareness is characterized by a "crisis-driven" approach to health literacy, with knowledge often gained through medical trauma rather than proactive education. Due to large gaps in the recognition of neurological and congenital symptoms, a comprehensive change toward nursing-led, family-centered counseling is required. NDS modules should be integrated into routine immunization schedules to improve infant survival rates and shorten recognition times.

Abstract: The rapid advancement of generative AI and large language models challenges long‑held assumptions about the purposes, content, methods, and practices of education. This paper integrates historical educational philosophy with contemporary AI capabilities to present a comprehensive framework for rethinking what and how we teach and learn. Drawing on foundational purposes—moral formation, democratic citizenship, critical emancipation, human capital development, and holistic flourishing—we analyse how AI’s strengths (pattern recognition, content generation) and limitations (lack of understanding, moral agency, empathy, metacognition) reshape educational priorities. We propose a curriculum of seven human‑irreplaceable competencies, including algorithmic literacy, ethical judgment, creative abduction, metacognition, emotional intelligence, systems thinking, and foundational knowledge and memorization. For learners, we identify six core skills: learning to learn, judge, create, relate, work with and without AI, and be. Pedagogically, we advocate eight principles: cognitive apprenticeship, problem‑based learning, critical AI literacy across disciplines, dual readiness, dialogic instruction, authentic assessment, teacher vulnerability, and deliberate memory building. For students, we outline eight practices: prompt‑critique‑synthesise, attention management, documentation, collaboration, questioning, deliberate AI‑free routines, productive struggle, and retrieval practice. A central argument is that while AI surpasses humans in memorisation and routine information retrieval, human learners must still internalise a durable core of knowledge to enable creativity, social cohesion, character development, and resilience in AI‑absent scenarios. The paper concludes that the AI era demands not the abandonment of traditional educational aims but their recalibration toward uniquely human capacities, with teachers and learners becoming co‑inquirers in an AI‑augmented but human‑centred ecosystem.

Abstract: Scientific recognition is only weakly determined by the intrinsic quality of research. A large body of work in the sociology of science, bibliometrics, and the emerging science of science instead describes recognition as a networked, cumulative-advantage process: attention concentrates on work that is already visible, early advantages compound, and most papers attract little notice regardless of merit. This review synthesizes that literature across three layers. First, it surveys the structural mechanisms — the social construction of recognition, heavy-tailed citation distributions and preferential attachment, the Matthew effect and reputation thresholds, the asymmetry of credit in team science, and the timing of individual impact. Second, it reviews the evidence on deliberate dissemination interventions — open access, preprints, plain-language summaries, targeted outreach, social-media presence, and the activation of weak ties — distinguishing well-supported effects from contested ones. Third, it examines how large language models and generative search are becoming a new amplifier of cumulative advantage, with measured citation biases toward already-prominent work and a growing share of science-related information seeking mediated by generative engines. Throughout, the central implication is that visibility is an actionable, channel-dependent outcome rather than an automatic byproduct of quality. We close by considering where automated scholarly-visibility services fit within this evidence base, and we identify open questions for research on visibility in the generative-search era.This review was written by Boris Gorelik of Loud Camel — Academic Career Promotion, a service that operationalizes several of the dissemination practices reviewed here as a recurring workflow; its conclusions rest on the cited literature, not on the service.

Abstract: Personality research has traditionally focused on stable trait differences, but emerging perspectives suggest that personality coherence, as the degree of integration versus heterogeneity across trait dimensions, may represent a critical aspect of self-functioning, with implications for behavioral regulation. The present study examined whether intraindividual variability in Big Five traits, operationalized as the within-person standard deviation across trait scores (iSD), is associated with problematic digital engagement in young adults. A sample of 316 completed the Big Five Inventory and selected subscales of the Behavioral Addiction Questionnaire assessing smartphone and internet use. Pearson correlations and independent samples t-tests were conducted to evaluate associations between personality structure and digital behaviors. Results showed that higher iSD, reflecting lower personality coherence, was significantly associated with greater problematic smartphone (r = .335, p = .021) and internet use (r = .383, p = .006). Participants in the problematic smartphone use group exhibited significantly higher iSD than those in the moderate-risk group. Accordingly, a less coherent personality structure may reflect increased internal instability, leading individuals to rely more on digitally mediated environments such as external regulatory systems providing predictability and reinforcement. Overall, the study highlights the importance of considering intraindividual personality configuration as a complementary dimension to traditional trait-based approaches.

Abstract: For over a century, the printed textbook has assumed learner homogeneity, creating persistent inequities for students with diverse reading levels, languages, and cultural backgrounds. Open Educational Resources (OER) offer a free, openly licensed alternative, yet most OER remain static documents requiring manual teacher differentiation. The rapid maturation of generative artificial intelligence (AI) provides a transformative solution: dynamic, AI‑powered OER that can be personalised at the point of use while preserving open licences. This quasi‑experimental design‑based research study developed, implemented, and evaluated a prototype called “AI‑OER Studio” over six months. Following a focus group with 12 educational technology experts to derive design principles, we built a web prototype that generates textbook chapters on any topic, at specified grade levels, in multiple languages, with culturally adapted examples, all under a CC BY‑SA 4.0 licence. [Legal disclaimer: the copyright status of AI‑generated content remains unresolved; see main text.] Expert reviewers (n=12) rated generated content favourably for factual accuracy (4.15/5) and pedagogical alignment (4.40/5), though bias scores were lower (3.95/5). A classroom pilot with 78 seventh‑grade students compared AI‑dynamic OER against static OER over a four‑week ecosystems unit. Students in the treatment group showed significantly higher learning gains (post‑test 78% vs. 68%; adjusted effect size d = 0.44 after accounting for classroom clustering) and spent 35 more minutes per week engaged, although a novelty effect likely accounts for some of this difference. Teacher interviews revealed substantial time savings but also concerns about factual hallucinations and cultural biases. The static textbook is increasingly ill‑suited for diverse classrooms; the future lies in living, AI‑augmented, openly licensed resources, provided that human validation, bias mitigation, and legal clarity are prioritised.

Abstract: This article examines the strategic intersection between agricultural heritage conservation and sustainable rural development by analyzing the Serra da Canastra cheese-producing microregion in Minas Gerais, Brazil. Following the historic inclusion of Artisanal Minas Cheese on UNESCO’s Intangible Cultural Heritage of Humanity list in late 2024, a significant structural disconnect persists between the product’s elevated global cultural reputation and the localized economic returns realized by traditional family farms. Utilizing a comparative mixed-methods approach, this study evaluates institutional frameworks, policy documents, and territorial data against the benchmark model of Italy’s Parmigiano Reggiano region. The findings indicate that international heritage designations do not automatically yield regional economic resilience; rather, symbolic value must be actively converted through coordinated multilevel governance. To capture sustainable growth, Brazilian stakeholders must transition from formal Geographical Indication (GI) compliance to an integrated system of experiential agri-tourism routes, strict collective quality enforcement via producer consortia, and landscape-driven narrative marketing. This paper contributes a transferable, transnational framework for policymakers and rural sociologists seeking to leverage cultural heritage assets as drivers of sustainable territorial development and economic diversification.

Abstract: Safety science generally does not rely on classic “threshold values” for physical injury, unlike the field and science of Occupational Hygiene. While such thresholds have been set for chemical, physical, biological, and ergonomic hazards, the psychosocial environment lacks similar analytical rigor. This study examines the concept of psychosocial threshold values or psychosocial exposure limits (PSEL). Utilizing a two-year longitudinal survey (N(2024) = 4912, N(2025) = 3035), stressors were coded as risk threshold (scores >3 on a 1–5 scale) and analyzed via logistic regression to predict work injuries resulting in absence from work. Results indicate that psychosocial factors were associated with significantly higher odds of injury (cross-sectional) after controlling for demographics and risk level. Persistent exposure was associated with higher Odds Ratios for injury in 2025 for an aggressive environment (OR = 2.83, CI 95% 1.75–4.59), organizational hindrances (OR = 1.88, CI 95% 1.21–2.91), and cognitive overload (OR = 1.5, CI 95% 1.14–1.97). Summing the psychosocial factors revealed a 56% increased risk of injury for each additional factor to which the worker was exposed. These findings suggest that organizational stressors can be modeled as predictive risk factors, with a threshold for monitoring and targeted interventions to mitigate future accidents, though further scale refinement for each variable is necessary to improve diagnostic and threshold accuracy.

Abstract: Despite the dramatic advances made in artificial intelligence (AI) and other fields of computer science towards implementing “intelligent” systems expert in specific tasks, the goal of devising algorithms and machines able to interact with human beings just as naturally as other humans do is still elusive. As this naturalness is arguably a consequence of the similarity of the underlying ‘hardware’ (the human brain), it is reasonable to claim that only artificial systems closely inspired by the actual functioning of the human brain and mind have the potential to render this possible. More specifically, the aim of this paper is to propose a new, biologically inspired computational model able to mimic, in a more accurate way than existing ones, the set of functionalities know as Theory of Mind. This is a set of mental processes that allow an individual to attribute mental states to others. In human social interactions this mechanism is crucial, as it allows one to explain the observed behaviour of others, to guess their intentions and to effectively predict their future conduct. This happens by modelling and selecting the most likely (unobservable) mental states of the considered person, which are the primary causes of everyone’s observed actions. The proposed model combines a number of concepts, including those of hierarchical structure, hypotheses pre-activation, and the notion of agent class or ‘stereotype’. It rests on one of the main psychological approaches to Theory of Mind, termed Simulation Theory (ST), and is supported by significant neuroscientific evidence. Crucially, unlike previous efforts in AI, the proposed model puts the learning element at the forefront, in the belief that simulations of other intelligent being’s reasoning processes need to be learned from experience. In this perspective, a possible implementation of the model in terms of deep, reconfigurable neural networks, trained in a reinforcement learning setting, is outlined.

Abstract: Coastal communities dependent on marine resources face chronic and acute threats from harmful algal blooms (HABs) that demand effective institutional responses. Resilience offers a useful framework for assessing how communities monitor, respond to, and adapt to these hazards, as well as how the institutions they have developed shape those capacities. Historically, affected communities have developed institutions to mitigate these hazards, making institutional resilience a valuable analytic lens. This paper adopts a comparative perspective to examine institutional measures for preventing and mitigating HABs in coastal waters. Using a most-similar-systems design, it analyzes institutional resilience-building measures in four democracies with distinct institutional configurations: the United States, Australia, Norway, and Japan. By distinguishing between ex ante (proactive) and ex post (reactive) measures and comparing responses to tempo-rally similar HAB events, the analysis identifies institutions as key explanatory variables shaping risk assessment, monitoring uptake, and policy effectiveness. Evaluating HAB governance through a resilience lens provides planners and decision-makers with a practical basis for developing a more balanced portfolio of responses in a dynamic hazard environment. This analysis suggests that sustained investment in a balanced approach – one that incorporates proactive measures – offers the most effective strategy for strengthening long-term adaptive capacity in confronting the hazard posed by HABs.

Abstract: Education for Sustainability (EfS) has emerged as a key response through which higher education engages ecological, social, and civic challenges. While EfS is well represented in policy and conceptual scholarship, fewer empirical studies examine how faculty enact sustainability within everyday teaching practice. This qualitative collective case study investigates the lived experiences and pedagogical practices of four faculty members at a U.S. land-grant university. Data were collected through semi-structured interviews, supported by syllabi, observations, and student responses, and analyzed using cross-case thematic analysis. Analysis identified four interconnected themes: latent complexity, personal commitment, inclusive scholarship, and adaptability to student motivations and context. These themes position EfS as a relational, context-responsive process shaped through interaction among faculty identity, student engagement, and institutional conditions. These findings reposition faculty practice as a primary mechanism through which sustainability is continuously enacted, adapted, and sustained within higher education systems, with implications for institutional policy, faculty development, and long-term sustainability capacity.

Abstract: Haitian women did not wait for the advent of modern contraceptive methods to manage their fertility. They developed strategies of resistance in the face of multifaceted patriarchal surveillance and medical neocolonialism. This study explores the regenerative and restorative practices underlying both the exclusive use of and the return to natural contraception. Methods: As part of a survey on fertility management in Haiti, I conducted remote interviews with six women and one man (the husband of one of the women surveyed) living in rural areas. Lasting between 60 and 90 minutes, the interviews were conducted in Haitian Creole using a semi-structured approach from June 18 to July 1, 2024. The responses to the various questions were recorded on the participants’ phones, with the exception of two interviews, which were recorded on my laptop (Windows Voice Recorder). Results: The study highlights that the exclusive use of and return to herbal contraceptives are primarily due to the negative effects of chemical contraceptive methods on marital relationships and the sexual and physical health of rural women. Conclusions: This study has the merit of showing that traditional healers and their clients do not confine themselves to a passive role in the face of patriarchal, marital, and religious scrutiny, among other forms of oversight. Contrary to biomedical and colonial prejudices, many of them are well informed about the existence of certain modern contraceptive methods and the negative consequences of these methods on their physical, psychological, and sexual health.

Abstract: Complete neighbourhoods — places where residents can meet most daily needs on foot — have become a cornerstone of healthy and sustainable urban planning. Yet most assess-ment frameworks were calibrated for dense metropolitan environments, leaving rural and peri-urban municipalities without operational tools suited to their territorial realities. This article presents MilieuxVie, an open-source, browser-based interactive mapping applica-tion developed for the Laurentides health region of Québec (76 municipalities, 11 land-based unorganised territories, 2 indigenous territories and 4 aquatic administrative units; 93 territorial units in total; ~680,000 inhabitants). The tool evaluates the spatial ac-cessibility of 12 service categories drawn from the Vivre en Ville (2026) com-plete-neighbourhood framework and OpenStreetMap data, using residential parcels from the provincial property assessment roll (MAMH 2026) as origin points and weighting re-sults by number of dwelling units. Three adaptive radius tiers (urban, intermediate, rural) based on municipal area correct for the systematic under-performance of standard thresholds in low-density settings. A dedicated Urban Perimeter mode further disaggre-gates analysis to sub-municipal built-up zones, aligning the tool with Québec's provincial planning orientations (OGAT). Gap analysis outputs identify which service types fall be-low the 70 % coverage target, enabling evidence-based prioritization for elected officials and planners. Results illustrate the scope of accessibility deficits across the region and highlight the analytical limits of uniform distance thresholds when applied beyond met-ropolitan contexts. The tool is freely available and requires no software installation, mak-ing it directly deployable by local planning offices.