JOURNAL ARTICLE

Grassroots leadership and negotiation style: The quest for justice in the movie Erin Brockovich.

  • Published In: Catalan Journal of Communication & Cultural Studies, 2023, v. 15, n. 2. P. 197 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Dash, Amarendra Kumar; Behera, Rashmi Ranjan; Dash, Rajendra Kumar 3 of 3

Abstract

The article analyzes the American film *Erin Brockovich* (2000) as a case study highlighting negotiation as a critical tool for achieving environmental justice amid socioenvironmental conflicts marked by power imbalances. It examines how the protagonist, Erin Brockovich, an unqualified legal clerk, evolves into a charismatic grassroots leader who successfully negotiates a $333 million settlement against Pacific Gas & Electric Company (PG&E) for chromium-6 groundwater contamination in Hinkley, California. The study situates Brockovich's negotiation style within frameworks of distributive negotiation, procedural justice, and environmental leadership, emphasizing her personal traits, emotional intelligence, and strategic process orientation as sources of her negotiating power. While acknowledging the film's dramatization and limitations in portraying legal complexities, the article underscores its influence on public awareness and environmental activism, suggesting that negotiation, combined with individual moral commitment and grassroots mobilization, remains vital for pursuing justice in environmental conflicts.

Additional Information

  • Source:Catalan Journal of Communication & Cultural Studies. 2023/10, Vol. 15, Issue 2, p197
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2023
  • ISSN:1757-1898
  • DOI:10.1386/cjcs_00088_1
  • Accession Number:172872441
  • Copyright Statement:Copyright of Catalan Journal of Communication & Cultural Studies is the property of Intellect Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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