Startseite Examining the Policy Learning Dynamics of Atypical Policies with an Application to State Preemption of Local Dog Laws
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Examining the Policy Learning Dynamics of Atypical Policies with an Application to State Preemption of Local Dog Laws

  • Michael P. Fix ORCID logo EMAIL logo und Joshua L. Mitchell ORCID logo
Veröffentlicht/Copyright: 19. Dezember 2017
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Abstract

Most of the literature on policy diffusion focuses on palpable issues such as economic or morality policies. As such, we know little about the mechanisms of diffusion for preemption of atypical policies such as animal regulations that lack a clear economic or ideological motivation. In this article, we propose and test a theory of conditional policy learning to explain the diffusion of atypical policies. We posit that a type of policy learning is occurring here, but that states only look to their neighbors when certain policy specific factors are present in their state. His theory is then applied to examine the dynamics of state adoption of laws preempting local Breed Specific Legislation from 1988 to 2014. Using an exponential model, two policy learning and two conditional learning hypotheses are tested. This study finds that policy learning is occurring through both external and internal pathways. This advances the literature by demonstrating that preemption occurs through the learning mechanism, but this learning effect is conditioned on policy relevant factors within the state.

Appendix 1: Descriptive Statistics

Table A1:

Descriptive statistics.

MeanStandard deviationMinimumMaximum
Neighboring adopters0.1900.1860.0000.800
Similar neighbor adopter0.1510.3580.0001.000
Bite fatalities4.7975.1580.00026.000
Dog fighting cases2.6036.6020.00047.000
% in Poverty12.7143.7492.90027.200
Urbanization68.65914.36932.20094.400
% Black0.1070.1690.0023.170
Median income50,445.2307828.11531,363.00074,118.000
South0.3090.4620.0001.000
Citizen ideology50.10915.3578.45095.972
Elite ideology51.54123.9153.01792.451
Divided government0.7790.4150.0001.000

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Published Online: 2017-12-19
Published in Print: 2017-12-20

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Heruntergeladen am 27.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/spp-2017-0009/html
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