arbiter
JournalsPricingAccount

Narrating the Loser: Theorizing the Role of Characters Within the Narrative Policy Framework

Rachel McGovern et al.

Policy Studies Journal2026https://doi.org/10.1111/psj.70105article
AJG 3ABDC B
Weight
0.50

What the paper says

ABSTRACT This paper explores the significance of characters within the Narrative Policy Framework (NPF), addressing the foundational question of their role and purpose in policy narratives. We argue that characters not only serve descriptive functions but are also strategically employed to shape the relationship between policy problems and policy solutions. Through this lens, we identify a gap in the current character typology. While NPF scholarship has established victims, villains, heroes, and beneficiaries as key characters in narratives, we introduce the loser . The loser character is not directly involved in the policy problem but is adversely affected by the policy solution. Our research is guided by three aims: to theorize the purpose of characters, clarify their narrative functions in relation to policy problems and solutions, and formally introduce the loser as a new character archetype.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1111/psj.70105

Or copy a formatted citation

@article{rachel2026,
  title        = {{Narrating the Loser: Theorizing the Role of Characters Within the Narrative Policy Framework}},
  author       = {Rachel McGovern et al.},
  journal      = {Policy Studies Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/psj.70105},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Narrating the Loser: Theorizing the Role of Characters Within the Narrative Policy Framework

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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.