title: The role of dispositional mindfulness in employee readiness for change during the COVID-19 pandemic

authors: Roemer, Anja

subjects: readiness for change

abstract: Purpose
The coronavirus disease 2019 (COVID-19) pandemic has forced organisations to change the way they work to maintain viability, even though change is not always successfully implemented. Multiple scholars have identified employees' readiness for change as an important factor of successful organisational change, but research focussed on psychological factors that facilitate change readiness is scarce. The purpose of the present study was to investigate whether employee dispositional mindfulness contributes to readiness for change.

Design/methodology/approach
Employees (n = 301) from various industries in New Zealand participated in an online survey shortly after the local COVID-19 lockdown ended. The employees' levels of mindfulness, readiness for change, well-being and distress were assessed using well-validated psychometric scales. Multiple regression analyses tested the effect of mindfulness on readiness for change, with well-being and distress as moderating variables.

Findings
The results show that the effect of mindfulness on readiness for change is moderated by both well-being and distress. Mindfulness has a positive, significant effect on readiness for change when levels of well-being are high and levels of distress are low.

Practical implications
These findings have important implications for organisations who aim to promote readiness for change in their employees. Even though mindfulness has been shown to be beneficial, organisations also have to consider the mental states of their employees when managing change.

Originality/value
This study provides empirical evidence that dispositional mindfulness may facilitate the employees' readiness for change, but only when levels of well-being are high and distress are low.

text: The role of dispositional mindfulness in employee readiness for change during the COVID-19 pandemic Purpose
The coronavirus disease 2019 (COVID-19) pandemic has forced organisations to change the way they work to maintain viability, even though change is not always successfully implemented. Multiple scholars have identified employees' readiness for change as an important factor of successful organisational change, but research focussed on psychological factors that facilitate change readiness is scarce. The purpose of the present study was to investigate whether employee dispositional mindfulness contributes to readiness for change.

Design/methodology/approach
Employees (n = 301) from various industries in New Zealand participated in an online survey shortly after the local COVID-19 lockdown ended. The employees' levels of mindfulness, readiness for change, well-being and distress were assessed using well-validated psychometric scales. Multiple regression analyses tested the effect of mindfulness on readiness for change, with well-being and distress as moderating variables.

Findings
The results show that the effect of mindfulness on readiness for change is moderated by both well-being and distress. Mindfulness has a positive, significant effect on readiness for change when levels of well-being are high and levels of distress are low.

Practical implications
These findings have important implications for organisations who aim to promote readiness for change in their employees. Even though mindfulness has been shown to be beneficial, organisations also have to consider the mental states of their employees when managing change.

Originality/value
This study provides empirical evidence that dispositional mindfulness may facilitate the employees' readiness for change, but only when levels of well-being are high and distress are low.

year: 2021

title: A study of hierarchical and flat classification of proteins

authors: Zimek, Arthur

subjects: computer science

abstract: Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that expert-defined hierarchies of protein classes exist and can potentially be exploited to improve classification performance. In this article we investigate empirically whether this is the case for two such hierarchies. We compare multi-class classification techniques that exploit the information in those class hierarchies and those that do not, using logistic regression, decision trees, bagged decision trees, and support vector machines as the underlying base learners. In particular, we compare hierarchical and flat variants of ensembles of nested dichotomies. The latter have been shown to deliver strong classification performance in multi-class settings. We present experimental results for synthetic, fold recognition, enzyme classification, and remote homology detection data. Our results show that exploiting the class hierarchy improves performance on the synthetic data, but not in the case of the protein classification problems. Based on this we recommend that strong flat multi-class methods be used as a baseline to establish the benefit of exploiting class hierarchies in this area.

text: A study of hierarchical and flat classification of proteins Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that expert-defined hierarchies of protein classes exist and can potentially be exploited to improve classification performance. In this article we investigate empirically whether this is the case for two such hierarchies. We compare multi-class classification techniques that exploit the information in those class hierarchies and those that do not, using logistic regression, decision trees, bagged decision trees, and support vector machines as the underlying base learners. In particular, we compare hierarchical and flat variants of ensembles of nested dichotomies. The latter have been shown to deliver strong classification performance in multi-class settings. We present experimental results for synthetic, fold recognition, enzyme classification, and remote homology detection data. Our results show that exploiting the class hierarchy improves performance on the synthetic data, but not in the case of the protein classification problems. Based on this we recommend that strong flat multi-class methods be used as a baseline to establish the benefit of exploiting class hierarchies in this area.

year: 2008

title: Cultural justice and ethics: From within

authors: Garner, Kerin

subjects: Maori

abstract: Where I eventually got a lot of support, awhi, aroha, was from the PPTA when I became a member of Te Huarahi and they helped to see me through the tears and the confusion. It wasn’t because I was Maori, it was because I was a human being. I think the process I have gone through is a process of becoming human, and becoming real in thinking; yes, my experience is valid. I’m not just Maori, I’m Pakeha too. I want both of them, I am both of them. I don’t have to get up and speak fluent Maori right now. Perhaps it will come. I hope it does because I want it to, and I’m going to work on it. But I do feel that people like me, and there are many of us, are not marginal. We are bridges between cultures. This diversity has to be acknowledged, honoured and respected.

text: Cultural justice and ethics: From within Where I eventually got a lot of support, awhi, aroha, was from the PPTA when I became a member of Te Huarahi and they helped to see me through the tears and the confusion. It wasn’t because I was Maori, it was because I was a human being. I think the process I have gone through is a process of becoming human, and becoming real in thinking; yes, my experience is valid. I’m not just Maori, I’m Pakeha too. I want both of them, I am both of them. I don’t have to get up and speak fluent Maori right now. Perhaps it will come. I hope it does because I want it to, and I’m going to work on it. But I do feel that people like me, and there are many of us, are not marginal. We are bridges between cultures. This diversity has to be acknowledged, honoured and respected.

year: 1993