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<p>Wellbeing is a crucial policy outcome within sustainable development, yet it can be measured and conceptualised in various ways. Methodological decisions, such as how different components are weighted, can influence wellbeing classification. Many studies utilise equal weighting, assuming each component is equally important; however, does this reflect communities’ lived experiences? This study outlines a multidimensional basic needs deprivation measure constructed from the Deltas, Vulnerability and Climate Change: Migration and Adaptation&#xa0;(DECCMA) survey dataset in Volta Delta, Ghana. Participatory focus groups, interviews and weighting exercises with communities and District Planning Officers (DPOs) explore different subgroups’ wellbeing priorities. Comparative analysis examines the weights provided across genders, decision-making levels and livelihoods; including farming, fishing and peri-urban groups. Objective survey data is also combined with various subjective weights to explore the sensitivity of the overall deprivation rate and its spatial distribution. Significant weight differences are found between livelihoods, with farming and fishing communities weighting “employment”, “bank access”, and “cooperative membership” higher, whereas peri-urban communities apply a greater weight to “healthcare access”. Differences between decision-making levels are also noted. Community members weight “employment” higher, while DPOs assign a larger score to “cooperative membership”. In contrast, consistent weights emerge across genders. Furthermore, applying community livelihood weights produces lower deprivation rates across most communities compared to DPO or equal nested weights. Overall, significant differences between subgroups’ weights and the sensitivity of wellbeing measurement to weighting selection illustrate the importance of not only collecting local weights, but also <i>where and whom</i> you collect weightings from matters.</p>

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“Where and Whom You Collect Weightings from Matters…” Capturing Wellbeing Priorities Within a Vulnerable Context: A Case Study of Volta Delta, Ghana

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月11日

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  • Laurence Cannings,
  • Craig W Hutton,
  • Kristine Nilsen,
  • Alessandro Sorichetta

摘要

Wellbeing is a crucial policy outcome within sustainable development, yet it can be measured and conceptualised in various ways. Methodological decisions, such as how different components are weighted, can influence wellbeing classification. Many studies utilise equal weighting, assuming each component is equally important; however, does this reflect communities’ lived experiences? This study outlines a multidimensional basic needs deprivation measure constructed from the Deltas, Vulnerability and Climate Change: Migration and Adaptation (DECCMA) survey dataset in Volta Delta, Ghana. Participatory focus groups, interviews and weighting exercises with communities and District Planning Officers (DPOs) explore different subgroups’ wellbeing priorities. Comparative analysis examines the weights provided across genders, decision-making levels and livelihoods; including farming, fishing and peri-urban groups. Objective survey data is also combined with various subjective weights to explore the sensitivity of the overall deprivation rate and its spatial distribution. Significant weight differences are found between livelihoods, with farming and fishing communities weighting “employment”, “bank access”, and “cooperative membership” higher, whereas peri-urban communities apply a greater weight to “healthcare access”. Differences between decision-making levels are also noted. Community members weight “employment” higher, while DPOs assign a larger score to “cooperative membership”. In contrast, consistent weights emerge across genders. Furthermore, applying community livelihood weights produces lower deprivation rates across most communities compared to DPO or equal nested weights. Overall, significant differences between subgroups’ weights and the sensitivity of wellbeing measurement to weighting selection illustrate the importance of not only collecting local weights, but also where and whom you collect weightings from matters.