title: Three-way interaction effects of workaholism on employee well-being: Evidence from blue-collar workers in New Zealand

authors: Haar, Jarrod M.

subjects: workaholism

abstract: Workaholism is an important workplace phenomenon that has received less empirical testing than might be expected. This study of 100 New Zealand blue-collar workers tested whether three dimensions of the workaholism triad: work involvement, drive to work and work enjoyment were related to anxiety, depression and insomnia, and in the majority this was supported. Work involvement was positively related to all outcomes, while work enjoyment was negatively related. Drive to work was positively related to anxiety and insomnia only. Overall, consistently, large amounts of variance were explained by the workaholism triad. While previously untested in the literature, a three-way interaction of the workaholism triad was found towards anxiety and insomnia. Overall, higher work involvement was useful in buffering detrimental outcomes for those with either high work involvement or high drive to work, but not both. The present study provides a new way of understanding the effects of workaholism in the workplace.

text: Three-way interaction effects of workaholism on employee well-being: Evidence from blue-collar workers in New Zealand Workaholism is an important workplace phenomenon that has received less empirical testing than might be expected. This study of 100 New Zealand blue-collar workers tested whether three dimensions of the workaholism triad: work involvement, drive to work and work enjoyment were related to anxiety, depression and insomnia, and in the majority this was supported. Work involvement was positively related to all outcomes, while work enjoyment was negatively related. Drive to work was positively related to anxiety and insomnia only. Overall, consistently, large amounts of variance were explained by the workaholism triad. While previously untested in the literature, a three-way interaction of the workaholism triad was found towards anxiety and insomnia. Overall, higher work involvement was useful in buffering detrimental outcomes for those with either high work involvement or high drive to work, but not both. The present study provides a new way of understanding the effects of workaholism in the workplace.

year: 2013

title: Experiments in cross-domain few-shot learning for image classification: extended abstract

authors: Wang, Hongyu

subjects: computer science

abstract: We summarise experiments (Wang et al., 2022) evaluating cross-domain few-shot learning (CDFSL) with feature extractors trained on ImageNet. The work explores the transfer performance of extracted features on five target domains with different degrees of similarity to ImageNet. These experiments compare robust classifiers and normalisation methods, consider multi-instance learning algorithms, and evaluate the effect of using features extracted by different ResNet backbones at various levels of their convolutional hierarchies. The cosine similarity classifier and 1-vs-rest logistic regression with ℓ2 regularisation are the top-performing robust classifiers in the evaluation, and ℓ2 normalisation improves performance on all five target domains when using LDA as the robust classifier. The results also show that feature extractors with the highest capacity do not always achieve the best CDFSL performance. Lastly, simple multi-instance learning methods are shown to improve classifier accuracy.

text: Experiments in cross-domain few-shot learning for image classification: extended abstract We summarise experiments (Wang et al., 2022) evaluating cross-domain few-shot learning (CDFSL) with feature extractors trained on ImageNet. The work explores the transfer performance of extracted features on five target domains with different degrees of similarity to ImageNet. These experiments compare robust classifiers and normalisation methods, consider multi-instance learning algorithms, and evaluate the effect of using features extracted by different ResNet backbones at various levels of their convolutional hierarchies. The cosine similarity classifier and 1-vs-rest logistic regression with ℓ2 regularisation are the top-performing robust classifiers in the evaluation, and ℓ2 normalisation improves performance on all five target domains when using LDA as the robust classifier. The results also show that feature extractors with the highest capacity do not always achieve the best CDFSL performance. Lastly, simple multi-instance learning methods are shown to improve classifier accuracy.

year: 2022

title: Restorative Practices in Schools: Far-Reaching Implications

authors: Drewery, Wendy

subjects: New Zealand

abstract: In 1999, the New Zealand Ministry of Education contracted a team from the University of Waikato to develop a process for conferencing in schools. The brief was to utilise restorative justice principles to develop a conferencing process for use in schools. The purpose was to test whether such an approach to wrongdoing could reduce the exponential increase of suspensions, particularly of Maori boys, who were, and still are, disproportionately represented in reported numbers of suspensions, stand-downs and exclusions.

text: Restorative Practices in Schools: Far-Reaching Implications In 1999, the New Zealand Ministry of Education contracted a team from the University of Waikato to develop a process for conferencing in schools. The brief was to utilise restorative justice principles to develop a conferencing process for use in schools. The purpose was to test whether such an approach to wrongdoing could reduce the exponential increase of suspensions, particularly of Maori boys, who were, and still are, disproportionately represented in reported numbers of suspensions, stand-downs and exclusions.

year: 2007