Policymaking at the intersection of identities: an identity-based policy framework

M. Khosravi et al.

Policy Design and Practice2026https://doi.org/10.1080/25741292.2025.2611626article
AJG 2
Weight
0.50

What the paper says

Traditional public policy, which is based on the assumption of citizen homogeneity, has often failed to address deep-seated structural inequalities. This article introduces the emerging paradigm of “identity-based policymaking” as an alternative framework that enables the transition from simplistic and uniform models to accountable and equitable governance in diverse and fragmented societies. By integrating theoretical foundations including social identity theory, the social construction of target populations, and the intersectionality framework, this framework places social identities at the center of policy analysis, design, and evaluation. By presenting the identity-instrument fit matrix as a prescriptive model and utilizing the latent class analysis method to scientifically identify latent target groups, the article argues that the effectiveness, efficiency, and acceptability of a policy depend on the alignment of its instrument logic with the dominant identity logic in the target population. Empirical evidence from various fields such as the environment, health, and agriculture proves the practical superiority of this approach compared to traditional models and its ability to achieve substantive justice.

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https://doi.org/https://doi.org/10.1080/25741292.2025.2611626

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@article{m.2026,
  title        = {{Policymaking at the intersection of identities: an identity-based policy framework}},
  author       = {M. Khosravi et al.},
  journal      = {Policy Design and Practice},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/25741292.2025.2611626},
}

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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.