Brent Doberstein

Brent Doberstein

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 November 2018 in Natural Hazards
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Journal Article
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BDBrent Doberstein
Brent Doberstein
JFJoanne Fitzgibbons
Joanne Fitzgibbons
CMCarrie Mitchell
Carrie Mitchell

1 October 2021 in Environmental Science & Policy
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Journal Article
Closed access
MCMahed-Ul-Islam Choudhury
Mahed-Ul-Islam Choudhury
CHC. Emdad Haque
C. Emdad Haque
BDBrent Doberstein
Brent Doberstein

1 September 2021 in Journal of Cleaner Production
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Journal Article
Closed access
IZIrina Safitri Zen
Irina Safitri Zen
AAAbul Quasem Al-Amin
Abul Quasem Al-Amin
Md. Mahmudul AlamMd. Mahmudul Alam
Md. Mahmudul Alam
BDBrent Doberstein
Brent Doberstein

1 January 2020 in Journal of Environmental Management
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Journal Article
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BDBrent Doberstein
Brent Doberstein
ATAnne Tadgell
Anne Tadgell
ARAlexandra Rutledge
Alexandra Rutledge

1 December 2021 in AMBIO
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Journal Article
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MAMichelle Anagnostou
Michelle Anagnostou
BDBrent Doberstein
Brent Doberstein

23 November 2021 in Disaster Prevention and Management: An International Journal
Verified
Journal Article
Closed access
C. Emdad HAQUEC. Emdad HAQUE
C. Emdad HAQUE
FBFikret Berkes
Fikret Berkes
ÁFÁlvaro Fernández-Llamazares
Álvaro Fernández-Llamazares
HRHelen Ross
Helen Ross
FIF. Stuart Chapin Iii
F. Stuart Chapin Iii
DHDavid Hutton
David Hutton
Purpose: The plethora of contributions to social learning has resulted in a wide range of interpretations, meanings and applications of social learning, both within and across disciplines. However, advancing the concept and using social learning methods and tools in areas like disaster-shocks requires interdisciplinary consolidation of understandings. In this context, the primary focus of this paper is on the contributions of social learning to disaster risk reduction (DRR).Design/methodology/approach: By applying a three-round policy Delphi process involving 18 purposefully selected scholars and expert-practitioners, the authors collected data on the meanings of social learning for two groups of professionals, DRR and social-ecological resilience. The survey instruments included questions relating to the identification of the core elements of social learning and the prospects for enhancing social-ecological resilience.Findings: The results revealed strong agreement that (1) the core elements of social learning indicate a collective, iterative and collaborative process that involves sharing/networking, changes in attitudes and knowledge and inclusivity; (2) social learning from disasters is unique; and (3) linkages between disciplines can be built by promoting interdisciplinarity, networks and knowledge platforms; collaboration and coordination at all levels; and teaching and practicing trust and respect. Social learning is useful in preparing for and responding to specific disaster events through communication; sharing experience, ideas and resources; creating synergies for collective action and promoting resilience.Research limitations/implications: The policy Delphi process involved a limited number of participants to control the quality of the data. To the best of the authors’ knowledge, this paper is the first of its kind to identify the core elements of social learning, specifically, in the disaster-shock context. It also makes significant contributions to the interdisciplinary integration issues.Practical implications: The practical implications of this study are related to pre-disaster planning and mitigation through the application of social learning on disaster-shocks.Social implications: The social implications of this study are related to valuing social learning for the improvement of disaster planning, management, and policy formulation and implementation in reducing disaster risks.Originality/value: The study provides a consensus view on the core elements of social learning and its role in DRR and resilience building. Relevant to all stages of DRR, social learning is best characterized as a collective, iterative and collaborative process. It can be promoted by enhancing networking and interdisciplinarity.