title: Whose future? Whose choosing?: Counselling in a context of (im)possible choice.

authors: Kotzé, Elmarie

subjects: school counselling

abstract: Critically reflexive practice is at the heart of counselling, and even more so when clients come face to face with (im)possible choices. As counsellor educators, the authors show counselling practice at the edge of uncertainty. This article features a counselling context in a secondary school. It describes a fictional situation where action is called for in the midst of undecidability, at an impasse in the life of a young woman client. The article explores the aporia that confront the young woman and the counsellor, in the context of education, career, families, cultures and communities. The authors show that these explorations produced transformational questions for their teaching practice as counsellor educators.

text: Whose future? Whose choosing?: Counselling in a context of (im)possible choice. Critically reflexive practice is at the heart of counselling, and even more so when clients come face to face with (im)possible choices. As counsellor educators, the authors show counselling practice at the edge of uncertainty. This article features a counselling context in a secondary school. It describes a fictional situation where action is called for in the midst of undecidability, at an impasse in the life of a young woman client. The article explores the aporia that confront the young woman and the counsellor, in the context of education, career, families, cultures and communities. The authors show that these explorations produced transformational questions for their teaching practice as counsellor educators.

year: 2011

title: Domain specific transfer learning using image mixing and stochastic image selection

authors: Coup, Sheldon

subjects: computer science

abstract: Can a gradual transition from the source to the target dataset improve knowledge transfer when fine-tuning a convolutional neural network to a new domain? Can we use training examples from general image datasets to improve classification on fine-grained datasets? We present two image similarity metrics and two methods for progressively transitioning from the source dataset to the target dataset when fine-tuning to a new domain. Preliminary results, using the Flowers 102 dataset, show that the first proposed method, stochastic domain subset training, gives an improvement in classification accuracy compared to standard fine-tuning, for one of the two similarity metrics. However, the second method, continuous domain subset training, results in a reduction in classification performance.

text: Domain specific transfer learning using image mixing and stochastic image selection Can a gradual transition from the source to the target dataset improve knowledge transfer when fine-tuning a convolutional neural network to a new domain? Can we use training examples from general image datasets to improve classification on fine-grained datasets? We present two image similarity metrics and two methods for progressively transitioning from the source dataset to the target dataset when fine-tuning to a new domain. Preliminary results, using the Flowers 102 dataset, show that the first proposed method, stochastic domain subset training, gives an improvement in classification accuracy compared to standard fine-tuning, for one of the two similarity metrics. However, the second method, continuous domain subset training, results in a reduction in classification performance.

year: 2019

title: E Kui Rāwinia

authors: Maxwell, Te Kahautu

abstract: E Kui Rāwinia; this composition is a lament to a Te Whakatōhea chieftainess who married the paramount Ngāti Porou rangatira Tokorua (Toko) Te Kani. This composition recites the genealogical ties between the East Coast iwi to Te Whakatōhea. The composition paints a spiritual journey for Rāwinia to return to her birth place Ōpōtiki. The journey names geographical features of importance to map her journey home. This composition gained first place for composition. Performed by Ōpōtiki Mai Tawhiti at the Te Matatini World Championship Kapa Haka competition.

text: E Kui Rāwinia E Kui Rāwinia; this composition is a lament to a Te Whakatōhea chieftainess who married the paramount Ngāti Porou rangatira Tokorua (Toko) Te Kani. This composition recites the genealogical ties between the East Coast iwi to Te Whakatōhea. The composition paints a spiritual journey for Rāwinia to return to her birth place Ōpōtiki. The journey names geographical features of importance to map her journey home. This composition gained first place for composition. Performed by Ōpōtiki Mai Tawhiti at the Te Matatini World Championship Kapa Haka competition.

year: 2015