This study examined the structural mechanisms and asymmetric normative frameworks through which comprehensive
economic sanctions, using the United States embargo against Cuba (1962–present) as the primary paradigmatic case,
function as instruments of political coercion in the contemporary international order. Drawing on a cross-national
dataset of 63 sanctioned states spanning the period 1990–2023, the study employed a multi-method quantitative
approach integrating univariate descriptive statistics, bivariate Pearson correlation analysis, binary logistic regression
modelling, and systematic data visualization to interrogate the relationships between coercion intensity, economic
performance, human development outcomes, and the duration of sanction regimes. The principal findings revealed a
statistically significant and strongly negative correlation between the Economic Coercion Index (ECI) and GDP per
capita (r = −0.712, p < 0.001), Human Development Index scores (r = −0.681, p < 0.001), and trade volume as a
proportion of GDP (r = −0.638, p < 0.001), while demonstrating significant positive associations with poverty rates (r
= 0.694, p < 0.001) and inflation (r = 0.521, p < 0.001). The logistic regression model, which demonstrated strong
predictive validity (AUC = 0.874; Nagelkerke R² = 0.612), confirmed that coercion intensity, duration of sanctions,
and GDP per capita were the most powerful independent predictors of severe economic contraction, controlling for
trade openness and institutional repression. The comparative panel analysis across eight case states, including Cuba,
Iran, North Korea, and Venezuela, demonstrated that comprehensive sanctions of prolonged duration uniformly
produced the most severe socioeconomic outcomes, disproportionately affecting civilian populations rather than
governing elites. The study concluded that the Cuban embargo, far from constituting a legitimate instrument of
democratization or security coercion, operates as a structural mechanism of civilizational suffocation — reinforcing
asymmetric international power relations and producing demonstrable human development deficits inconsistent with
stated foreign policy objectives. The study recommended multilateral reform of sanctions governance frameworks,
the introduction of binding humanitarian carve-out protocols, and the adoption of sunset clauses to enforce periodic
evidence-based review of extended embargo regimes.

This study critically assessed Uganda's readiness to integrate Artificial Intelligence (AI) in teaching and learning
environments across secondary and tertiary educational institutions. Anchored in the Technology Acceptance Model
(TAM) and the Concerns-Based Adoption Model (CBAM), the study employed a cross-sectional survey design
involving 420 teachers and educators drawn from 42 purposively selected schools and universities across five regions
of Uganda. Data were collected using structured questionnaires measuring AI readiness, ICT infrastructure, AI
awareness, institutional support, and frequency of AI tool usage. Employing a three-tier analytical framework —
univariate descriptive statistics, bivariate Pearson correlations, and multilevel regression modelling — the study
revealed a national mean AI readiness score of 47.3 (SD = 15.2), indicating moderate but highly unequal readiness
levels across geographic and institutional divides. Institutions in Kampala recorded significantly higher readiness
scores (M = 74.6) compared to Northern Uganda (M = 27.3), reflecting deeply entrenched structural inequalities. ICT
infrastructure (β = 0.48, p < 0.001), AI awareness (β = 3.72, p < 0.001), and institutional support (β = 2.15, p < 0.001)
emerged as the strongest predictors of AI readiness. Multilevel modelling confirmed significant school-level variance
(ICC = 0.213), indicating that 21.3% of the variability in AI readiness was attributable to between-school differences
rather than individual teacher characteristics. The study concludes that Uganda's education system is at a nascent and
inequitable stage of AI integration, and recommends urgent policy reforms targeting infrastructure investment,
educator capacity building, and national AI curriculum frameworks to ensure equitable and transformative AI-driven
education for all Ugandans.

Background: Artificial intelligence-driven platforms increasingly mediate social interaction through hyperpersonalized content delivery, raising concerns about their effects on individualism and social cohesion. Despite
growing recognition of AI's social impacts, systematic understanding of mechanisms through which algorithmic
personalization promotes individualistic orientations and reconfigures traditional social structures remains limited.
Objective: This study examined how AI technologies promote individualism and transform social fabric by
investigating: (1) mechanisms through which AI personalization algorithms foster individualistic behaviors and
worldviews; (2) effects of AI-mediated individualism on community participation, civic engagement, and social
solidarity; and (3) differential impacts across demographic groups and cultural contexts.
Methods: A cross-sectional mixed-methods study was conducted between March 2024 and January 2025 across five
countries (USA, UK, Japan, South Korea, Uganda) representing varying individualism-collectivism orientations.
Using stratified random sampling, 2,847 participants aged 18-65 years who regularly used AI-driven platforms
completed structured questionnaires measuring AI usage intensity, platform diversity, personalization awareness,
individualistic orientation (0-100 scale), social cohesion index, and demographic characteristics. Data analysis
employed univariate descriptive statistics, bivariate analysis (chi-square tests, t-tests, ANOVA, correlation analysis),
and multivariate modeling including binary logistic regression predicting high individualism and multinomial logistic
regression predicting social cohesion levels, with interaction terms examining cultural context moderation effects.
Results: Univariate analysis revealed significant cross-national variations in AI usage (M=24.3 hrs/week overall;
range: 18.9-28.7), individualism scores (M=62.4; range: 52.1-71.8), and social cohesion (M=54.7; range: 48.2-64.3),
with Western countries demonstrating higher AI usage and individualism but lower social cohesion (all p

Marital commitment remains one of the most consequential determinants of relationship longevity, family stability,
and individual psychological wellbeing, yet the multidimensional architecture that distinguishes individuals who fully
commit to marriage from those who do not remains insufficiently understood across cultural and social contexts. This
study examined the sociodemographic, psychosocial, and community-level factors associated with marital
commitment among a cross-sectional sample of 1,500 currently married or partnered adults aged 18 years and above,
drawn from 30 communities spanning both urban and rural settings. Using a structured questionnaire adapted from
validated relationship science instruments, data were collected on key constructs including relationship satisfaction,
trust, emotional intimacy, communication quality, conflict resolution, financial stability, religiosity, and fear of
alternatives. Univariate analysis revealed that 66.7% of respondents were classified as highly committed, while 33.3%
exhibited low commitment profiles. Bivariate analysis using independent samples t-tests demonstrated statistically
significant differences between committed and uncommitted respondents across all psychosocial variables (p < 0.001),
with the largest effect sizes observed for relationship satisfaction (d = 0.82), trust (d = 0.84), and emotional intimacy
(d = 0.79). Binary logistic regression identified relationship satisfaction (OR = 2.32), trust in partner (OR = 2.14), and
emotional intimacy (OR = 2.03) as the strongest individual-level predictors of commitment, alongside significant
contributions from tertiary education (OR = 1.79), age group 35–44 (OR = 1.68), and religious values (OR = 1.51).
Fear of available alternatives was the only significant negative predictor (OR = 0.64). Multilevel modelling further
revealed that community-level factors — including community religiosity, urbanization, and collective education
levels — accounted for approximately 11.1% of the variance in commitment status in the null model (ICC = 0.111),
which was substantially reduced to 3.3% upon inclusion of both individual and community predictors in the full model,
indicating that individual-level factors are the primary drivers of commitment while community context provides a
meaningful but secondary modulating influence. The study concludes that marital commitment is a multidimensional
phenomenon shaped by the interplay of emotional, cognitive, social, and structural forces, and recommends targeted
psychoeducational couple interventions, structural policy support for relationship health, and community-based
programmes that leverage religiosity and social networks to strengthen marital bonds.

Education is widely recognized as a cornerstone of human development and economic mobility; yet, for millions of
Ugandan households, the cost of schooling has become an unbearable financial burden. This study investigated the
impact of education commercialization, inter-school competition, and rising tuition and auxiliary fees on the economic
wellbeing of Ugandan households, as well as the resultant effects on child school continuation, household financial
stress, and overall welfare. A cross-sectional survey design was employed, drawing on a systematically sampled
population of 400 household heads across urban and peri-urban districts of Uganda. Data were collected using
structured questionnaires and subjected to univariate frequency analysis, bivariate ANOVA and Pearson correlation
analysis, and Structural Equation Modeling (SEM) using maximum likelihood estimation. Results revealed that the
majority of low-income households (55.8% earning below UGX 700,000 per month) allocated over 48% of their
monthly income to educational expenditures, with households in the lowest income bracket spending up to 62.4% of
their budgets on schooling. ANOVA revealed statistically significant differences in educational expenditure across
income groups (F(3, 396) = 47.81, p < 0.001, η² = 0.266). Pearson correlation analysis confirmed significant negative
associations between education expenditure and household wellbeing (r = −0.587, p < 0.01) and between household
income and child drop-out rates (r = −0.518, p < 0.01). SEM results demonstrated that competition-driven school fees
had a significant direct effect on education expenditure (β = 0.581, p < 0.001) and on education-induced financial
stress (β = 0.612, p < 0.001), which in turn significantly reduced household wellbeing (β = −0.555, p < 0.001) and
increased child drop-out rates (β = 0.503, p < 0.001). The model exhibited excellent fit indices (CFI = 0.962, RMSEA
= 0.048). The study concluded that the commercialization of education is systematically eroding household economic
resilience and undermining equitable access to quality education in Uganda. The study recommended targeted fee
regulation mechanisms, means-tested scholarship programs, and the strengthening of government capitation grants as
immediate policy imperatives.

The proliferation of digital platforms and the advent of citizen journalism have fundamentally restructured the global
media landscape, lowering barriers to entry and democratizing the production and dissemination of news content.
While this transformation has expanded public voices and challenged traditional gatekeeping, it has simultaneously
precipitated a measurable erosion of core journalistic principles — including accuracy, editorial independence, source
transparency, and ethical accountability. This study examined the relationship between media democratization and the
decline of journalistic norms, with particular focus on how structural, technological, and institutional factors mediate
this relationship. Employing a cross-sectional survey research design, data were collected from 320 respondents
comprising professional journalists, citizen journalists, media educators, and frequent news consumers drawn from
diverse media environments. Univariate, bivariate, and Structural Equation Modelling (SEM) analyses were
conducted using SPSS version 26 and AMOS version 24. Findings revealed statistically significant negative
associations between democratization indices and ethical adherence scores (r = −0.52, p < 0.001). The SEM results
confirmed that media democratization exerted a strong direct effect on the erosion of journalistic norms (β = 0.61, p
< 0.001), which in turn significantly predicted both public trust deficits (β = 0.67, p < 0.001) and misinformation
spread (β = 0.58, p < 0.001). The model demonstrated excellent fit (CFI = 0.96; RMSEA = 0.048; SRMR = 0.051).
These results underscore the urgent need for regulatory frameworks, professional capacity-building, and platform
accountability mechanisms to preserve journalistic integrity in an increasingly democratized media environment. The
study recommends the establishment of inclusive professional standards bodies, mandatory digital media literacy
programmes, and algorithmic accountability protocols to mitigate the adverse effects of journalism's democratization
on public discourse and democratic governance.

Background: Contemporary society is characterized by unprecedented levels of social surveillance and judgment,
intensified by digital technologies that enable constant observation and evaluation. While philosophical traditions
have long recognized the tensions between social conformity and authentic living, limited empirical research has
examined how perpetual judgment specifically constrains autonomy and well-being in digitally connected
populations.
Objective: This study examined the impact of perpetual social judgment on individual authenticity and psychological
well-being, investigating the mechanisms through which the social gaze operates and identifying conditions that
enable authentic living in contemporary contexts.
Methods: A mixed-methods convergent parallel design was employed with 847 participants aged 18-65 years
recruited through stratified random sampling from urban and semi-urban settings. Data were collected using validated
psychometric instruments measuring authenticity, social anxiety, psychological well-being, and social media intensity,
alongside researcher-developed items assessing perceived social judgment and conformity behaviors. Quantitative
analysis included univariate descriptive statistics, bivariate Pearson correlations, and binary logistic regression
predicting high authenticity. Additionally, 32 semi-structured interviews provided qualitative insights into lived
experiences of navigating social expectations.
Results: Univariate analysis revealed that 51.4% of participants reported low authenticity, with moderately elevated
social anxiety (M=34.67, SD=11.23) and moderate psychological well-being (M=64.82, SD=15.47). Social media
intensity was notably high (M=4.83, SD=1.56), with 77.9% of participants engaging at moderate to high levels.
Bivariate correlations demonstrated strong negative relationships between authenticity and social anxiety (r=-.612,
p

This study examined the paradox of natural resource abundance and chronic underdevelopment in Africa — a
phenomenon widely theorised as the "resource curse" — through a rigorous political economic lens spanning 20
African countries over the period 2000 to 2022. Despite holding approximately 30% of the world's mineral reserves
and a substantial share of global hydrocarbon deposits, most resource-rich African nations continued to register lower
human development indices, weaker governance scores, greater income inequality, and slower rates of structural
economic transformation relative to their resource-poor counterparts on the continent. The study was anchored on
three core objectives: to assess the statistical relationship between natural resource dependence and key development
outcomes; to evaluate the moderating role of governance quality on this relationship; and to model the projected
developmental impact of alternative structural transformation scenarios. Employing a mixed-methods analytical
strategy, the study generated panel data for 20 countries across 23 years, yielding 1,380 country-year observations.
Univariate descriptive statistics established the baseline distributional characteristics of key variables including GDP
per capita, the Human Development Index (HDI), resource rents as a proportion of GDP, World Bank Governance
Indicators (WGI), GINI coefficients, and manufacturing sector output. Bivariate Pearson correlation analyses revealed
statistically significant negative associations between resource rent dependency and both HDI (r = −0.489, p < 0.001)
and governance quality (r = −0.612, p < 0.001), while manufacturing output showed a strong positive correlation with
GDP per capita (r = 0.716, p < 0.001). Three-level random effects regression models — incorporating country-level
and year-level fixed effects alongside cross-level interaction terms — confirmed that resource rent dependency exerted
a significant negative effect on the composite development index (β = −0.176, p < 0.001) even after controlling for
income levels, governance, inequality, and foreign direct investment. Critically, the interaction of resource rents with
governance quality (β = −0.158, p < 0.001) demonstrated that poor institutional environments substantially amplified
the curse effect, while manufacturing sector expansion significantly buffered against it. Policy simulation scenarios
further projected that a combined strategy of governance reform, manufacturing expansion, and reduced resource rent
dependency could yield a 16.4% improvement in composite development outcomes, rising to 25.4% under a full
structural transformation scenario. These findings reinforced the theoretical propositions of the Dutch Disease model,
the rentier state hypothesis, and heterodox structuralist development theory. The study concluded that Africa's resource
curse was neither inevitable nor permanent, but was fundamentally a governance and structural transformation failure
that demanded decisive, state-led industrial policy, institutional reform, and regional economic integration as the
imperative pathway forward.

This study examined the paradox of postcolonial elites in African higher education institutions, drawing on the
rhetorical and philosophical critiques advanced by Pan-African orator Patrick Loch Otieno (PLO) Lumumba. Framed
within decolonial theory and critical pedagogy, the study interrogated how African academic elites simultaneously
espoused decolonial rhetoric while perpetuating Western epistemological frameworks, a contradiction captured in the
metaphor of the 'one-eyed king'—one who sees only through the lens of the former coloniser. A mixed-methods
research design was employed, incorporating a structured survey administered to 320 academic staff drawn from six
universities across Sub-Saharan Africa. Statistical methods including univariate descriptive analysis, bivariate Pearson
correlation, and binary logistic regression were applied to examine patterns, associations, and predictors of critical
pedagogical practice. Findings revealed that the Elite Contradiction Index (ECI) was negatively and significantly
associated with decolonial orientation and curriculum Africanisation, while the Western Credential Index (WCI)
emerged as a significant predictor of reduced critical pedagogical engagement. Decolonial Orientation Score (DOS)
and Curriculum Africanisation Score (CAS) were the strongest positive predictors of critical pedagogical practice in
the logistic regression model. The study concluded that structural, ideological, and credentialing factors converge to
sustain elite contradiction in postcolonial African universities, and that intentional decolonial policy reforms are
necessary to align institutional rhetoric with practice. The study recommended reforms in faculty development,
curriculum policy, and leadership accountability frameworks to bridge the gap between decolonial discourse and
educational reality in Africa.

Background: Religious explanatory frameworks predominate in African contexts, where spiritual, divine, and
supernatural causation often serve as primary lenses for interpreting socioeconomic phenomena including health,
poverty, education, and economic outcomes. While religion provides undeniable spiritual and social benefits, concerns
have emerged regarding potential socioeconomic ramifications when religious attributions eclipse empirical,
structural, and systemic analyses of social challenges.
Objective: This study critically analyzed the relationship between religious explanatory primacy and socioeconomic
outcomes in African contexts, examining mechanisms through which religious attribution patterns influenced
development trajectories.
Methods: A cross-sectional study was conducted between January and August 2024 across Nigeria, Kenya, and
Ghana, employing multistage sampling to recruit 1,500 adult respondents (500 per country) from urban and rural
communities. Data were collected through structured questionnaires measuring religious explanatory primacy via a
validated 20-item Religious Attribution Scale and socioeconomic outcomes using standardized indices for healthseeking behavior, educational investment, entrepreneurial orientation, and poverty alleviation strategies. Statistical
analysis proceeded through univariate descriptive statistics, bivariate correlations and chi-square tests, and Structural
Equation Modeling (SEM) to examine direct, indirect, and moderated relationships between constructs.
Results: Univariate analysis revealed that 63.3% of respondents exhibited high religious attribution (M=73.42,
SD=15.68), with 42.1% endorsing primarily prayer-focused poverty strategies and 35.4% prioritizing spiritual over
biomedical health approaches. Bivariate analysis demonstrated significant negative correlations between religious
attribution and health-seeking behavior (r=-0.412, p