.
Disaster management policy often privileges quantifiable impacts, yet non-economic losses and damages (NELDs) profoundly shape human and community well-being. This study examines NELDs in Chimanimani District, Zimbabwe, following Cyclone Idai, across four domains: (1) loss of life and health; (2) loss of place, belonging, and cultural identity; (3) disruption of social networks and collective memory; and (4) psychological and spiritual well-being. Using a mixed-methods approach that combines longitudinal ethnographic inquiry, in-depth qualitative interviews, and document analysis, the study explores the intangible, socially embedded, and culturally mediated dimensions of loss and damage that extend beyond material destruction. The findings reveal that extreme climate events generate significant emotional burdens and reshape social, cultural, and spiritual systems through which communities sustain collective life. By placing NELDs at the centre of analysis, the study advances a justice-centred approach to loss and damage, emphasising the need to embed distributional, procedural, and recognition justice in research and practice. Methodologically, longitudinal ethnography captures slow, complex, and culturally embedded losses, generating the nuanced insights necessary to inform context-sensitive policies and disaster governance that honour human dignity, cultural integrity, and social cohesion.
Indigenous cattle are central to livelihoods, climate resilience, and cultural systems in semi-arid regions, yet their phenotypic diversity is often insufficiently documented to support effective conservation and sustainable use improvement. The study aimed to classify officially recognized indigenous cattle breeds (Afrikaner, Mashona, and Tuli) based on their phenotypic characteristics. The study animals were selected randomly among the animals present at the plunge dip tank (a tick-control practice in which cattle are immersed in an acaricide solution) for three consecutive dipping’s, morphological and morphometric traits were observed and documented using a standardized breed characterization guideline. Three breeds (Afrikaner, Mashona, Tuli) and three classes (Cows, Heifers, Steers) were considered for this study, and a maximum of 9 animals for each class and breed was used. A stepwise discriminant analysis procedure was used to select the most significant variables, while canonical discriminant analysis was applied for breed classification. The morphometric data underwent factor analysis to capture the principal sources of variation, prioritizing factors with the highest variance. Multivariate statistical approaches, were applied as exploratory tools to identify traits contributing most strongly to phenotypic differentiation, while acknowledging sampling limitations The results showed that the morphometric trait variability was much higher (P < 0.001), the most essential traits for easy identification of cattle were HL, DBH, BW, RL HG, and EW, as evidenced by their partial discrete R2 values. The study produced two statistically significant canonical variables (P < 0.001), with CAN1 explaining 72.3
Restorative justice is integral to juvenile justice reform. However, social workers in Zimbabwe face systemic barriers in implementing the Pre-Trial Diversion (PTD) programme, which aims to rehabilitate juvenile offenders and protect their rights. This study aims to examine the barriers that hinder social workers’ effective participation in the implementation of Zimbabwe’s Pre-Trial Diversion (PTD) programme. Grounded in the restorative justice model and anti-oppressive social work principles, the research employed a qualitative design, using semi-structured interviews with 15 purposively sampled participants, including social workers and key informants in Chitungwiza District. Data analysis through NVivo 12 revealed five themes: fragmented legal frameworks, professional marginalization, resource constraints, limited diversion options, and insufficient stakeholder participation. Findings highlight that the absence of a Child Justice Bill of 2021 undermines restorative justice, while resource shortages and reliance on donor funding perpetuate systemic inefficiencies. Furthermore, social workers face marginalization within multi-sectoral teams, limiting their influence in diversion processes. Limited referral pathways and inadequate caregiver involvement further hinder the programme’s effectiveness. The study concludes that social workers must advocate for legislative reform, sustainable resource allocation, and expanded diversion options to address juveniles’ complex needs. Promoting collaboration among stakeholders and empowering caregivers to participate in restorative justice processes are essential. These findings underscore the need for systemic reforms, capacity building, and participatory approaches to strengthen social workers’ roles in advancing child-centred justice. By addressing these barriers, the PTD programme can fulfill its rehabilitative mandate, aligning with restorative justice principles and safeguarding children’s rights in Zimbabwe.
Children are some of the most vulnerable members of society who must be protected at all costs. Zimbabwe has a long history of disjointed formal and indigenous social protection systems, which have resulted in the exclusion of many children, leading to high levels of child abuse, neglect, exploitation and violence. In policy and practice, there is a strong bias towards the ineffective statist formal system, yet the indigenous social protection system is the mainstay for the protection of most children. The study aimed to explore how asset-based community development can be used as a strategy to integrate the fragmented formal and indigenous social protection systems for sustainable child protection. An explanatory sequential mixed-methods research design was employed, collecting both quantitative and qualitative data from 76 participants. The study findings indicate that asset-based community development by positioning the indigenous social protection system at the centre of the social protection framework provides a blueprint for a community-led and integrated social protection system, which can translate into effective child protection. This system, which utilises a wider network of community and external resources, can counteract the limits of fragmented social protection and sustainably promote child protection among impoverished households in Zimbabwe and similar contexts. The recommendation is that asset-based community development should be promoted as a strategy towards integrated social protection and sustainable child protection.
Quality is one of the most debated topics in the history of Qualitative Research Methods (QRM). It establishes the benchmarks, norms and values that a researcher should follow when involved in research. Quality is a critical tool for promoting value, effectiveness and efficiency in research processes. Qualitative research is popular in several disciplines such as local governance studies, sociology, education, gender studies, public management, media studies, human resource management, political science etc. The proponents of Qualitative Research (QR) believe that it has unique characteristics compared to quantitative and mixed research methods. Qualitative Research (QR) focuses on understanding lived experiences through narrative inquiry, field observations, focus study groups, and the use of digital photos. The literature on quality advocates for methodological rigor in QR. The discourse of quality in qualitative research is evolving with time and the evolving trends in technology and AI. This review explores the key characteristics of QR and the evolving trends. It provides a meta-summary of the quality benchmarks identified across the various domains of qualitative research literature. It evaluates the advantages and limitations of using Artificial Intelligence in QR. Findings from the literature revealed that there is scholarly attention on quality components: credibility, transferability, dependability, confirmability, and authenticity. The characteristics of qualitative research call for different quality standards such as trustworthiness, reflexivity, contextual sensitivity, and rigour. Overall, the findings indicate that embracing Artificial intelligence (AI) in Qualitative Research presents opportunities and threats. AI's ability to manage large-scale and multimodal data has enhanced the collection of qualitative data. AI can produce brief summaries or spot reoccurring patterns by offering real-time insights. The authors of this paper recommend that future studies should evaluate how quality standards in QR are interpreted and implemented across different academic disciplines, cultures and contexts.
