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Cited by 164

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

Predictable and Unpredictable Policy Windows: Institutional and Exogenous Correlates of Canadian Federal Agenda-Setting

Howlett, Michael·1998·Canadian Journal of Political Science

Abstract

This article addresses the question of the applicability of John Kingdon's theory of agenda-setting to Canadian political life. It examines the extent to which agenda-setting in Canadian governments is routine or discretionary, predictable or unpredictable, and the extent to which it is influenced by events and activities external to itself. The study uses time series data collected on issue mentions related to Native affairs, the constitution, drug abuse, acid rain, the nuclear industry and capital punishment in parliamentary debates and committees between 1977 and 1992. It compares these series to other time series developed from media mentions, violent crime rates, unemployment rates, budget speeches and speeches from the throne, elections and first ministers' conferences over the same period in order to assess the impact of such events on public policy agenda-setting.

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Metadata

Authors
Howlett, M.
Venue
Canadian Journal of Political Science
Published
1998-09
Volume
31
Issue
3
Pages
495-524
ISSN
  • 0008-4239 (ISSN-L)
  • 1744-9324
OpenAlex
W2048290759
Cited by
164
References
1
FWCI
2.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Predictable and Unpredictable Policy Windows: Institutional and Exogenous Correlates of Canadian Federal Agenda-Setting. https://app.cochat.ai/papers/10.1017/s0008423900009100
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Howlett, M. (1998). Predictable and Unpredictable Policy Windows: Institutional and Exogenous Correlates of Canadian Federal Agenda-Setting. Canadian Journal of Political Science. https://doi.org/10.1017/s0008423900009100

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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.