Bridging the health equity gap: examining the effects of water, sanitation and hygiene (WaSH) gender-based violence on health and wellbeing in Ghana
Notice bibliographique
Résumé
Access to water, sanitation and hygiene (WaSH) is widely recognized as an important pathway to promoting human health and wellbeing. Despite the progress in access to water and sanitation in Low-and Middle-Income Countries (LMIC), there are significant inequalities and disparities across space and place. Inequalities in WaSH access heighten women’s vulnerability to violence when meeting their WaSH needs. This represents a significant barrier to achieving the Sustainable Development Goals (SDGs) by 2030. For instance, it will not be possible to achieve health and wellbeing for all (SDG 3) without safe water and sanitation for all (SDG 6), and neither is it possible without empowering women (SDG 5). However, WaSH practitioners and researchers are yet to adequately conceptualize the gendered vulnerability to violence in WaSH for informed policy. \nThis thesis draws on an integrated theoretical framework to explore the relationships between WaSH access and gendered dimensions of vulnerabilities to violence in LMICs. The research focused on three broad objectives: first, to develop an integrated theoretical framework for framing our understanding of WaSH gender-based violence in Low-and Middle-Income Countries (LMICs); second, to characterize the dimensions of WaSH gender-based violence (WaSH-GBV) in LMICs; and finally, to explore the WaSH-GBV experiences of Ghanaian immigrants in Canada over the life course. A qualitative research approach – involving conceptual review, scoping review, and in-depth interviews –was used in the research. \nThe conceptual review proposes an integrated theoretical framework for understanding intersectional vulnerabilities such as gender-based violence and water insecurity in LMICs. This framework emphasizes the role of place and scale in the conceptualization of WaSH-GBV in LMICs. It argues that WaSH-GBV is a relational outcome, and our understanding of it is tied to how individuals, communities and institutions envision place and how their interactions are maintained over time. Results from the scoping review reveal four interrelated dimensions of WaSH-GBV in LMICs, including structural, physical, psychosocial, and sexual violence. Structural violence is mutually constitutive with the other dimensions of violence. Further, the in-depth interviews (n=27; 16 women and 11 men) reveal that individual understanding and perceptions of WaSH-GBV are complex, socially constructed and context-dependent. Participants’ narratives indicate that while WaSH-GBV may occur in one place, the psychosocial impacts are not bound to place and time. \nThis research makes significant contributions to knowledge, policy, and practice. Theoretically, the research demonstrates the utility of incorporating feminist political ecology with political ecology of health to form an integrated theoretical framework – feminist political ecology of health (FPEH) for a broader understanding of the multidimensional nature of WaSH-GBV and how contextual factors produce and reinforce experiences of violence across space and place. The framework is a useful tool for exploring how structural factors at different scales interact to shape gendered WaSH vulnerabilities in LMICs. The framework provides a robust platform for understanding the relationship between health in place and how health outcomes across scales (i.e., micro, meso and macro) are gendered. While the framework focuses on WaSH inequalities and vulnerabilities in LMICS, it is also useful in the context of developed countries and other research areas concerned with exploring health inequalities among populations. Methodologically, the research contributes to the conceptualization of WaSH-GBV in LMICs. The research also highlights the strengths of employing multiple qualitative methods such as scoping reviews and in-depth interviews for a broader understanding of WaSH-GBV in cross-cultural settings. In terms of policy, understanding WaSH-GBV as a relational outcome will facilitate global efforts on achieving SDGs: 3 – ensure good health and wellbeing for all; 5 – achieve gender equality and empower all women and girls; and 6 – ensure water and sanitation for all. The research also highlights the need for policies that are tailored and integrate community perspectives and experiences for promoting collective social change and community-led mobilization efforts that promote gender equality.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,007 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».