Understanding Intergroup Conflict Complexity: An Application of the Socioecological Framework and the Integrative Identity Negotiation Theory

Tenzin Dorjee & Stella Ting‐Toomey

Negotiation and Conflict Management Research2020https://doi.org/10.1111/ncmr.12190article
AJG 1ABDC C
Weight
0.57

What the paper says

Abstract This research article used a controversial in‐progress conflict case story, namely the Citizenship Amendment Act in India, to illustrate the benefit of using a combined socioecological framework and integrative identity negotiation theory in explaining intergroup conflict complexity. The essay is structured in four sections. First, we present a highly controversial conflict case story of the Citizenship Amendment Act (CAA) that was recently passed in India. The real‐life case story is embedded in the nexus of multifaceted identity conflict and multileveled socioecological interpretations. Second, we introduce the socioecological (SE) framework and its essential principles and illustrative examples of the various levels of analysis. Third, we review selective assumptions of the integrative identity negotiation theory (IINT) and, together with the SE framework, analyze the CAA India case story with explanatory depth and multilevel insights. Fourth, we conclude with a summary and seven strategy recommendations that can be applied to managing polarized intergroup conflict complexity constructively.

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https://doi.org/https://doi.org/10.1111/ncmr.12190

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@article{tenzin2020,
  title        = {{Understanding Intergroup Conflict Complexity: An Application of the Socioecological Framework and the Integrative Identity Negotiation Theory}},
  author       = {Tenzin Dorjee & Stella Ting‐Toomey},
  journal      = {Negotiation and Conflict Management Research},
  year         = {2020},
  doi          = {https://doi.org/https://doi.org/10.1111/ncmr.12190},
}

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Evidence weight

0.57

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.57 × 0.4 = 0.23
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.