Working from the Ground Up and Participatory Action Research: An old urban neighbourhood in Hong Kong

Fung, Kwok Kin; Chan, Yu Cheung; Hung, Suet Lin

doi:10.1080/10705422.2023.2181900

Cited by 2 publications

(1 citation statement)

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“…Additionally, it is important to measure the extent of community engagement on social media posts. This provides insights into the depth of interaction and the quality of engagement, which are critical for understanding the extent to which community members are connected and involved (Fung et al, 2023). This understanding is crucial for gauging the impact of social media engagement beyond mere visibility metrics such as views or likes.…”

Section: Digital Storytellingmentioning

confidence: 99%

A practical guideline for co-creating knowledge with migrant domestic workers using the photovoice method

Liem,

Utama,

Chen

et al. 2024

Preprint

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This article presents a guideline for the utilisation of the photovoice method to facilitate the collaborative generation of knowledge with migrant domestic workers (MDWs), integrating feminist participatory action research principles that promote participant involvement as knowledge co-creators. The guideline is the culmination of the authors' extensive participatory research with migrant workers, focusing on their mental health and social challenges. It provides a structured, step-by-step approach for conducting photovoice projects, from preparation to dissemination, emphasising MDWs' agency and expertise in their experiences. The guideline is designed to assist researchers, practitioners, and policymakers with essential tools for conducting research that meaningfully involves MDWs, with the goal of informing policies and interventions to enhance their lives and mental health. It is also a valuable tool for community organisations and advocacy groups seeking to use photovoice for social research and advocacy. The authors' collective experience in health research and the arts informs the guideline, ensuring a comprehensive and collaborative framework for its application.

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Section: Digital Storytellingmentioning

confidence: 99%