title: Collective writing: An inquiry into praxis

authors: Jandrić, Petar

subjects: collective writing

abstract: This is the second text in the series collectively written by members of the Editors' Collective, which comprises a series of individual and collaborative reflections upon the experience of contributing to the previous and first text written by the Editors' Collective: 'Towards a Philosophy of Academic Publishing.' In the article, contributors reflect upon their experience of collective writing and summarize the main themes and challenges. They show that the act of collective writing disturbs the existing systems of academic knowledge creation, and link these disturbances to the age of the digital reason. They conclude that the collaborative and collective action is a thing of learning-by-doing, and that collective writing seems to offer a possible way forward from the co-opting of academic activities by economics. Through detaching knowledge creation from economy, collaborative and collective writing address the problem of forming new collective intelligences.

text: Collective writing: An inquiry into praxis This is the second text in the series collectively written by members of the Editors' Collective, which comprises a series of individual and collaborative reflections upon the experience of contributing to the previous and first text written by the Editors' Collective: 'Towards a Philosophy of Academic Publishing.' In the article, contributors reflect upon their experience of collective writing and summarize the main themes and challenges. They show that the act of collective writing disturbs the existing systems of academic knowledge creation, and link these disturbances to the age of the digital reason. They conclude that the collaborative and collective action is a thing of learning-by-doing, and that collective writing seems to offer a possible way forward from the co-opting of academic activities by economics. Through detaching knowledge creation from economy, collaborative and collective writing address the problem of forming new collective intelligences.

year: 2017

title: Self-trained centroid classifiers for semi-supervised cross-domain few-shot learning

authors: Wang, Hongyu

abstract: State-of-the-art cross-domain few-shot learning methods for image classification apply knowledge transfer by fine-tuning deep feature extractors obtained from source domains on the small labelled dataset available for the target domain, generally in conjunction with a simple centroid-based classification head. Semi-supervised learning during the meta-test phase is an obvious approach to incorporating unlabelled data into cross-domain few-shot learning, but semi-supervised methods designed for larger sets of labelled data than those available in few-shot learning appear to easily go astray when applied in this setting. We propose an efficient semi-supervised learning method that applies self-training to the classification head only and show that it can yield very consistent improvements in average performance in the Meta-Dataset benchmark for cross-domain few-shot learning when applied with contemporary methods utilising centroid-based classification.

text: Self-trained centroid classifiers for semi-supervised cross-domain few-shot learning State-of-the-art cross-domain few-shot learning methods for image classification apply knowledge transfer by fine-tuning deep feature extractors obtained from source domains on the small labelled dataset available for the target domain, generally in conjunction with a simple centroid-based classification head. Semi-supervised learning during the meta-test phase is an obvious approach to incorporating unlabelled data into cross-domain few-shot learning, but semi-supervised methods designed for larger sets of labelled data than those available in few-shot learning appear to easily go astray when applied in this setting. We propose an efficient semi-supervised learning method that applies self-training to the classification head only and show that it can yield very consistent improvements in average performance in the Meta-Dataset benchmark for cross-domain few-shot learning when applied with contemporary methods utilising centroid-based classification.

year: 2023

title: An evaluation of the Raukawa Health Services Kaumatua Mirimiri Programme

authors: Gregg, Lisa

subjects: Maori

abstract: The Kaumatua Mirimiri Programme was funded as a Service to Improve Access project under a contract which ran from 1st September 2004 to 30th June 2005. Its aim was to provide a “culturally based treatment and recovery programme to restore the health and independence” of people aged 40 years and over (Pinnacle Group Ltd, 2004a, p.1). However, as the service specification in the contract made clear, the programme was not designed be exclusive: it has attracted younger as well as older people, non-Māori as well as Māori, and people seeking help for a wide range of ailments and pain.

text: An evaluation of the Raukawa Health Services Kaumatua Mirimiri Programme The Kaumatua Mirimiri Programme was funded as a Service to Improve Access project under a contract which ran from 1st September 2004 to 30th June 2005. Its aim was to provide a “culturally based treatment and recovery programme to restore the health and independence” of people aged 40 years and over (Pinnacle Group Ltd, 2004a, p.1). However, as the service specification in the contract made clear, the programme was not designed be exclusive: it has attracted younger as well as older people, non-Māori as well as Māori, and people seeking help for a wide range of ailments and pain.

year: 2006-03