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Enregistrement W2034005291 · doi:10.1080/13876980500116261

Regional Policy Agglomeration: Arctic Policy in Canada and the United States

2005· article· en· W2034005291 sur OpenAlex
Peter May, Bryan D. Jones, Betsi Beem, Emily Neff-Sharum, Melissa K. Poague

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no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
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Notice bibliographique

RevueJournal of Comparative Policy Analysis Research and Practice · 2005
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueArctic and Russian Policy Studies
Établissements canadiensnon disponible
Organismes subventionnairesNational Science Foundation
Mots-clésPoliticsPolitical sciencePublic policyIndigenousPublic administrationPolicy studiesDiversity (politics)ArcticScience policyPolicy SciencesLaw

Résumé

récupéré en direct d'OpenAlex

Abstract Regional policies addressing urban policy, rural policy and policies with specific regional targets tend to evolve from the consideration of disparate issues that impact the designated region rather than as co-ordinated strategies. We label this aggregation of disparate policies as policy agglomeration. We examine this phenomenon for domestic aspects of Arctic policies in Canada and the United States. Arctic policy in each setting is comprised of a diversity of policy components with limited policy targeting for the Arctic region or populations. The greater targeting of Canadian policies with respect to both place and indigenous populations is explained by institutional and political factors. Acknowledgements We thank Courtney Munson for invaluable research assistance and Josh Sapotichne and anonymous reviewers for helpful comments. Funding for this research was provided to the University of Washington by the National Science Foundation under grant no. OPP-0219543 under a project co-directed by Bryan D. Jones and Peter J. May. The findings of this research are not necessarily endorsed by the National Science Foundation or the University of Washington. Notes Peter J. May is Professor of Political Science at the University of Washington and a faculty associate of the Center for American Politics and Public Policy. His research addresses policy design and implementation. Bryan D. Jones is Donald Matthews Professor of Political Science and Director of the Center for American Politics and Public Policy at the University of Washington. His research addresses policy dynamics and decision-making. Betsi E. Beem, Emily A. Neff-Sharum and Melissa K. Poague are graduate fellows of the Center for American Politics and Public Policy at the University of Washington where each is completing a PhD. This discussion is based on a review of the issues raised in congressional hearings, conducted in 1982, prior to passage of the Arctic Research and Policy Act of 1984. The Canadian Polar Commission Act of 1991 defines "polar regions" in relation to Canada as including all areas north of 60 degrees north latitude and all areas north of the southern limit of the discontinuous permafrost zone. To assess whether this difference biased our findings, we compared mean policy centrality scores for the US data prior to 1996 with US data that are limited to the period of the Canadian statutes, 1996–2002. We failed to detect a difference in the mean centrality scores for these two sets of data (t-test = − 1.10, p = 0.27). This suggests that the different periods are comparable with respect to the key variable of interest in this study. The percentage of the statute devoted to Arctic considerations was estimated by coders, rather than calculated by counting lines or words. Any such count would have been problematic because of differences in the construction of statutes. Another way to measure this difference is to compare the respective distribution of centrality scores that are shown in Figure 1. These distributions also differ (Chi square = 9.78, p = .02). The mean centrality scores and one-tailed t-test for scores when comparing Canada and the United States respectively for environmental policies are 2.40 and 1.44 (t-test = 1.78, p = .05) and for development policies are 2.29 and 1.30 (t-test = 1.58, p = .08). The mean centrality scores and one-tailed t-test for centrality scores when comparing Canada and the United States respectively for human services policies are 1.79 and 1.45 (t-test = .95, p = .18). Another way to measure this difference is to compare the respective distribution of centrality scores that are shown in Figure 2. These distributions also differ (Chi square = 10.51, p = .02). Additional informationNotes on contributorsPeter J May Peter J. May is Professor of Political Science at the University of Washington and a faculty associate of the Center for American Politics and Public Policy. His research addresses policy design and implementation. Bryan D. Jones is Donald Matthews Professor of Political Science and Director of the Center for American Politics and Public Policy at the University of Washington. His research addresses policy dynamics and decision-making. Betsi E. Beem, Emily A. Neff-Sharum and Melissa K. Poague are graduate fellows of the Center for American Politics and Public Policy at the University of Washington where each is completing a PhD.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,008
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,871
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,006
Études des sciences et des technologies0,0010,002
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,141
Tête enseignante GPT0,493
Écart entre enseignants0,352 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle