Evidence map›Paper›PMID 36915801›Full record

ArticleGeoforum; journal of physical, human, and regional geosciences2023

Understanding livelihood changes in the charcoal and baobab value chains during Covid-19 in rural Mozambique: The role of power, risk and civic-based stakeholder conventions.

Judith E Krauss, Eduardo Castro, Andrew Kingman, Milagre Nuvunga, Casey Ryan

Abstract read
In one paragraph

Article in Geoforum; journal of physical, human, and regional geosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Judith E KraussUniversity of York, Department of Politics/Interdisciplinary Global Development Centre, Derwent College, Heslington, York YO10 5DD, UK.
Eduardo CastroUniversidade Eduardo Mondlane, Mozambique.
Andrew KingmanMicaia Foundation, Mozambique/UK.
Milagre NuvungaMicaia Foundation, Mozambique/UK.
Casey RyanUniversity of Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-pharmaceutical interventions (NPIs) to reduce the transmission of Covid-19 had different repercussions for domestic, regional and global value chains, but empirical data are sparse on specific dynamics, particularly on their implications for value-chain stakeholders' local livelihoods. Through research including weekly phone interviews (n = 273 from May to July 2020) with panellists in six Mozambican communities, our research traced firstly how the baobab and charcoal value chains were affected by Covid NPIs, particularly in terms of producers' livelihoods. Secondly, we ask how our findings advance our understanding of the role of civic-based stakeholder conventions and different types of power in building viable local livelihoods. Our conceptual lens is based on a synthesis of value-chain and production-network analysis, convention theory and livelihood resilience focusing on power and risk. We found that Covid trading and transport restrictions considerably re-shaped value chains, albeit in different ways in each value chain. The global baobab value chain continued to provide earnings particularly to women, when other income sources were eliminated, with socially oriented stakeholders altering their operations to accommodate pandemic restrictions. By contrast, producers involved in the domestic, solely market-oriented charcoal value chain saw their selling opportunities and incomes reduced, with hunger rising in charcoal-dependent communities. Our paper argues that local livelihoods were more resilient under Covid NPIs if civic-based conventions and collective, social power were present.

Indexed as

BaobabCharcoalConvention theoryCovid shockGlobal value chainsMozambiqueRural livelihoods

Identifiers

PMID36915801
PMCPMC9995225

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.