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Cited by 998

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Do regimes matter? Epistemic communities and Mediterranean pollution control

Haas, Peter M.·1989·International Organization

Abstract

International regimes have received increasing attention in the literature on international relations. However, little attention has been systematically paid to how compliance with them has been achieved. An analysis of the Mediterranean Action Plan, a coordinated effort to protect the Mediterranean Sea from pollution, shows that this regime actually served to empower a group of experts (members of an epistemic community), who were then able to redirect their governments toward the pursuit of new objectives. Acting in an effective transnational coalition, these new actors contributed to the development of convergent state policies in compliance with the regime and were also effective in promoting stronger and broader rules for pollution control. This suggests that in addition to providing a form of order in an anarchic international political system, regimes may also contribute to governmental learning and influence patterns of behavior by empowering new groups who are able to direct their governments toward new ends.

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Metadata

Authors
Haas, P. M.
Venue
International Organization
Published
1989
Volume
43
Issue
3
Pages
377-403
ISSN
  • 0020-8183 (ISSN-L)
  • 1531-5088
OpenAlex
W2123831532
Cited by
998
References
1
FWCI
91.87
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Do regimes matter? Epistemic communities and Mediterranean pollution control. https://app.cochat.ai/papers/10.1017/s0020818300032975
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Haas, P. M. (1989). Do regimes matter? Epistemic communities and Mediterranean pollution control. International Organization. https://doi.org/10.1017/s0020818300032975

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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.