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Institution

Hampshire College

EducationAmherst Center, Massachusetts, United States
About: Hampshire College is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Genetic programming & Population. The organization has 461 authors who have published 998 publications receiving 40827 citations.


Papers
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Journal ArticleDOI
James Miller1
30 Oct 2015
TL;DR: The Creative Citizens project as mentioned in this paper aims to identify practices that will exploit this new individual and collective activity, presumably as a means of achieving authentic self-governance, and considers three potential obstacles to the realization of a creative citizenship: that the sort of political engagement it fosters may be too personal and episodic; that the commonsensical political knowledge typical of politics known at a distance as performance and simulation may impose further limits on effective understanding and engagement; and that the emerging new media environment may be different enough that today's digital skills and relationships may be insufficient in the medium term.
Abstract: The Creative Citizens project asks whether new media enhance new forms and scale of creative civic activities. If so, the project seeks to identify practices that will exploit this new individual and collective activity, presumably as a means of achieving authentic self-governance. This paper considers three potential obstacles to the realization of a creative citizenship: that the sort of political engagement it fosters may be too personal and episodic; that the commonsensical political knowledge typical of politics known at a distance as performance and simulation may impose further limits on effective understanding and engagement; and that the emerging new media environment may be different enough that today’s digital skills and relationships may be insufficient in the medium term. The paper looks at the same conditions that inspire the creative citizenship project and reaches reverse conclusions – but not on the grounds of nostalgia or pessimism.

2 citations

Proceedings ArticleDOI
J.J. Davila1
08 Dec 2003
TL;DR: The results obtained are not only better than those for other typically used neural network topologies, but also better than for neural networks that incorporate music theory knowledge.
Abstract: This paper presents the results of using the GENDALC GANN system to evolve neural network topologies for music perception. The results obtained are not only better than those for other typically used neural network topologies, but also better than for neural networks that incorporate music theory knowledge. Because the data and task used in these experiments include hierarchical time dependent processing, these results demonstrate GENDALC's ability to evolve good solutions for cognitive tasks, even while using approaches potentially different from those used by humans.

2 citations

Journal ArticleDOI
Rachel Conrad1
TL;DR: In this article, the intersections of mothers' and children's desires and subjectivities are considered, and there is value in considering maternal presence and time in conjunction with children's sense of time and the present in order to imagine a relational time that both mothers and children construct.
Abstract: Daphne de Marneffe (2004) has enriched our theoretical understanding of maternal desire as fundamentally a desire to relate to or “be with” (p. xi) one's child. This view can enable consideration of children's subjectivity and agency through thinking about the intersections of mothers' and children's desires and subjectivities. Contemplating the meanings of maternal desire necessitates attending to multiple practices of mothering in a range of relational contexts. Finally, there is value in considering maternal presence and time in conjunction with children's sense of time and the present in order to imagine a relational time that both mothers and children construct.

2 citations


Authors

Showing all 467 results

NameH-indexPapersCitations
Anton Zeilinger12563171013
Peter K. Hepler9020721245
William H. Warren7634922765
James Paul Gee7021040526
Eric J. Steig6922317999
Raymond W. Gibbs6218817136
David A. Rosenbaum5119810834
Lee Jussim441159101
Miriam E. Nelson4412216581
Stacia A. Sower431786555
Howard Barnum411096510
Lee Spector391654692
Eric C. Anderson381065627
Alan H. Goodman341045795
Babetta L. Marrone33953584
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202221
202117
202034
201949
201833