Delimiting cross-border areas for policy implementation: a multi-factor proposal

Medeiros, Eduardo

doi:10.1080/09654313.2019.1687654

Cited by 16 publications

(7 citation statements)

References 44 publications

(37 reference statements)

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“…Alongside, there are several cross-border cooperation entities with the neighbour Spanish regions implemented since 1990 [47] in which all Alentejo municipalities are clustered, for instance in the participation of two Euroregions (EURO-ACE and EUROAAA). As expected, however, the municipalities adjacent to the Spanish borderline are more active in these cross-border cooperation processes and, hence, share similar development concerns [67]. Similarly, several border Innlandet' municipalities have established cross-border entities with the Swedish neighbour regions since the mid-1960s (Figure 11).…”

Section: Developmentsupporting

confidence: 54%

Development Clusters for Small Places and Rural Development for Territorial Cohesion?

Medeiros

2021

Sustainability

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This article proposes an alternative policy development approach for territories encompassing rural areas with small urban settlements or ‘small places’, which normally suffer from lagging territorial development trends. The proposed ‘Development Clusters for Small Places’ approach draws on the potential of all places to further their development via municipal clustering, based on four analytic dimensions: (i) existing functional areas; (ii) similarities in economic circularity and specialisation; (iii) presence of ongoing territorial and governance cooperation processes; and (iv) spatial physical connectivity and accessibility. Besides a theoretical overview of this policy approach, the article analyses concrete examples of its potential implementation in two case studies: Alentejo in Portugal and Innlandet in Norway. The findings highlight the potential advantages of municipal clustering over current mainstream regional development rationales to implement endogenous rural development in a supra-municipal scale, thus increasing institutional thickness and policy influence towards a more territorial cohesive region.

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Section: Developmentsupporting

confidence: 54%

Development Clusters for Small Places and Rural Development for Territorial Cohesion?

Medeiros

2021

Sustainability

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“…Scientific research devoted to territorial cooperation planning (Braunerhielm, Olsson & Medeiros, 2019; Durand & Decoville, 2018; Kurowska‐Pysz, Castanho & Loures, 2018) highlights the important issue of identifying the geographical boundaries of cross‐border cooperation areas. A number of factors are taken into account in the delimitation process, including historical, spatial, demographic, cultural, data, institutional, economic, infrastructural and environmental factors (Medeiros, 2019). In practice, however, the conditions for cross‐border cooperation at the EU’s external borders are so diverse that proposing a universal model of delimitation becomes impossible and requires an individual approach, adapted to the specificity of a given borderland (Studzieniecki, 2016).…”

Section: Cross‐border Cooperation In Scientific Researchmentioning

confidence: 99%

Key conditions for Euroregions development at external EU borders: A case study of the Polish–Belarusian borderland

Studzieniecki

Jakubowski

Meyer

2022

Regional Science Policy & Practice

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External borders of the European Union (EU) constitute a significant spatial and formal legal barrier for mutual relations. The key role in overcoming this barrier is played by cross‐border cooperation implemented by subnational units. The objective of this article is to identify key conditions for the cross‐border cooperation on the Polish–Belarusian border, constituting the external border of the EU. An additional objective is to develop a concept of institutionalization of the cross‐border cooperation, and to point to the possibilities of its implementation in the area of the Polish–Belarusian Euroregion Przybuże. This objective has been implemented by means of the triangulation method with the application of interrelated research techniques such as focus group interview, moderated workshop, surveys and desk research. The research discovered long‐term, intense cross‐border relations existing in the said region. The leaders of the cooperation were identified on both sides of the border. The institutionalization of this cooperation through the creation of the Euroregion was recognized by the stakeholders as an opportunity to dynamize social and economic development and to absorb EU funds more effectively. The developed concept of Euroregions creation and the case study analysis enrich the scientific output related to the theory of territorial cooperation, and offer practical solutions useful in the development of cross‐border areas, with particular consideration of regions located at the external borders of the EU.

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“…Language planning is closely related to language-ecological issues, such as language resources, diversity, and social functions. It is an essential national means for social governance and promoting social harmony [20][21][22]. In terms of minority language planning, China has formulated a series of minority language policies in the Xinjiang province at different historical stages.…”

Section: Cross-border Language Planning (Cblp)mentioning

confidence: 99%

Exploration of Cross-Border Language Planning Using the Graph Neural Network for Internet of Things-Native Data

Long

2022

Mobile Information Systems

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This work aims to study applying the graph neural network (GNN) in cross-border language planning (CBLP). Consequently, following a review of the connotation of GNN, it puts forward the research method for CBLP based on the Internet of Things (IoT)-native data and studies the classification of language texts utilizing different types of GNNs. Firstly, the isomorphic label-embedded graph convolution network (GCN) is proposed. Then, it proposes a scalability-enhanced heterogeneous GCN. Subsequently, the two GCN models are fused, and the research model-heterogeneous InducGCN is proposed. Finally, the model performances are comparatively analyzed. The experimental findings suggest that the classification accuracy of label-embedded GNN is higher than that of other methods, with the highest recognition accuracy of 97.37% on dataset R8. The classification accuracy of the proposed heterogeneous InducGCN fusion model has been improved by 0.09% more than the label-embedded GNN, reaching 97.46%.

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Delimiting cross-border areas for policy implementation: a multi-factor proposal

Cited by 16 publications

References 44 publications

Development Clusters for Small Places and Rural Development for Territorial Cohesion?

Development Clusters for Small Places and Rural Development for Territorial Cohesion?

Key conditions for Euroregions development at external EU borders: A case study of the Polish–Belarusian borderland

Exploration of Cross-Border Language Planning Using the Graph Neural Network for Internet of Things-Native Data

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