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Cited by 296

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Cooperative Regulatory Enforcement and the Politics of Administrative Effectiveness

Scholz, John T.·1991·American Political Science Review

Abstract

Even when political interests control bureaucratic outputs, the control of policy outcomes is complicated by trade-offs between controllable versus effective implementation strategies. I use a nested game framework to explain why a cooperative strategy can increase enforcement effectiveness in the narrow administrative game and why principal-agent control problems and collective action problems associated with the strategy lead policy beneficiaries to oppose the effective strategy in the broader political games. Analyses of state-level Occupational Safety and Health Administration enforcement provide evidence that cooperation does enhance the impact of enforcement in reducing workplace injury rates but that policy beneficiaries oppose and sabotage cooperation. The interactions between administrative effectiveness and interest group politics in this and other implementation situations require that both be analyzed simultaneously, and the nested game framework can provide a systematic approach to such analyses.

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Metadata

Authors
Scholz, J. T.
Venue
American Political Science Review
Published
1991-03
Volume
85
Issue
1
Pages
115-136
ISSN
  • 0003-0554 (ISSN-L)
  • 1537-5943
OpenAlex
W2104269187
Cited by
296
References
48
FWCI
22.07
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Cooperative Regulatory Enforcement and the Politics of Administrative Effectiveness. https://app.cochat.ai/papers/10.2307/1962881
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Scholz, J. T. (1991). Cooperative Regulatory Enforcement and the Politics of Administrative Effectiveness. American Political Science Review. https://doi.org/10.2307/1962881

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.