title: One size fits not quite all: Universal research ethics with diversity

authors: Msoroka, Mohamed Salum

subjects: Ethics

abstract: For researchers in Aotearoa New Zealand who intend to conduct research with people, it is common practice to first ensure that their proposals are approved by a Human Research Ethics Committee (HREC). HRECs take the role of reviewing, approving or rejecting research proposals and deciding on whether the intended research will be completed in the ‘right’, rather than the ‘wrong’ way. Such decisions are based upon a system which is guided by universal ethical principles – principles that assume there is universal agreement about the ethically right way to conduct research. Increasingly, Aotearoa New Zealand is becoming more culturally diverse. Actions that are assumed as ‘right’ in reference to ethical norms endorsed in one culture or society may not always be considered ‘right’ in reference to ethical norms in another culture or society. In this article we first set out what is already known in the literature about the origins and applications of universal ethics in a research context. Next, we analyse how cultural values and beliefs bear influence on the process of ethical deliberation. Two case studies illustrate our own examples of how conducting ethical research projects following universal principles with cultural diversity operated in practice. We conclude that one size fits not quite all. Lastly, we propose that Aotearoa New Zealand HRECs may need to consider expanding their approach from universal ethical principles to include a more diverse interpretation of what is ‘ethical research conduct’. Rather than advocating a radical approach, i.e. either universality or diversity, it is time for HRECs to consider a hybrid approach of universality with diversity that permits partial detour from universal principles when considering ethics application proposals.

text: One size fits not quite all: Universal research ethics with diversity For researchers in Aotearoa New Zealand who intend to conduct research with people, it is common practice to first ensure that their proposals are approved by a Human Research Ethics Committee (HREC). HRECs take the role of reviewing, approving or rejecting research proposals and deciding on whether the intended research will be completed in the ‘right’, rather than the ‘wrong’ way. Such decisions are based upon a system which is guided by universal ethical principles – principles that assume there is universal agreement about the ethically right way to conduct research. Increasingly, Aotearoa New Zealand is becoming more culturally diverse. Actions that are assumed as ‘right’ in reference to ethical norms endorsed in one culture or society may not always be considered ‘right’ in reference to ethical norms in another culture or society. In this article we first set out what is already known in the literature about the origins and applications of universal ethics in a research context. Next, we analyse how cultural values and beliefs bear influence on the process of ethical deliberation. Two case studies illustrate our own examples of how conducting ethical research projects following universal principles with cultural diversity operated in practice. We conclude that one size fits not quite all. Lastly, we propose that Aotearoa New Zealand HRECs may need to consider expanding their approach from universal ethical principles to include a more diverse interpretation of what is ‘ethical research conduct’. Rather than advocating a radical approach, i.e. either universality or diversity, it is time for HRECs to consider a hybrid approach of universality with diversity that permits partial detour from universal principles when considering ethics application proposals.

year: 2018

title: An entropy gain measure of numeric prediction performance

authors: Trigg, Leonard E.

subjects: computer science

abstract: Categorical classifier performance is typically evaluated with respect to error rate, expressed as a percentage of test instances that were not correctly classified. When a classifier produces multiple classifications for a test instance, the prediction is counted as incorrect (even if the correct class was one of the predictions). Although commonly used in the literature, error rate is a coarse measure of classifier performance, as it is based only on a single prediction offered for a test instance. Since many classifiers can produce a class distribution as a prediction, we should use this to provide a better measure of how much information the classifier is extracting from the domain. 
Numeric classifiers are a relatively new development in machine learning, and as such there is no single performance measure that has become standard. Typically these machine learning schemes predict a single real number for each test instance, and the error between the predicted and actual value is used to calculate a myriad of performance measures such as correlation coefficient, root mean squared error, mean absolute error, relative absolute error, and root relative squared error. With so many performance measures it is difficult to establish an overall performance evaluation.
The next section describes a performance measure for machine learning schemes that attempts to overcome the problems with current measures. In addition, the same evaluation measure is used for categorical and numeric classifier.

text: An entropy gain measure of numeric prediction performance Categorical classifier performance is typically evaluated with respect to error rate, expressed as a percentage of test instances that were not correctly classified. When a classifier produces multiple classifications for a test instance, the prediction is counted as incorrect (even if the correct class was one of the predictions). Although commonly used in the literature, error rate is a coarse measure of classifier performance, as it is based only on a single prediction offered for a test instance. Since many classifiers can produce a class distribution as a prediction, we should use this to provide a better measure of how much information the classifier is extracting from the domain. 
Numeric classifiers are a relatively new development in machine learning, and as such there is no single performance measure that has become standard. Typically these machine learning schemes predict a single real number for each test instance, and the error between the predicted and actual value is used to calculate a myriad of performance measures such as correlation coefficient, root mean squared error, mean absolute error, relative absolute error, and root relative squared error. With so many performance measures it is difficult to establish an overall performance evaluation.
The next section describes a performance measure for machine learning schemes that attempts to overcome the problems with current measures. In addition, the same evaluation measure is used for categorical and numeric classifier.

year: 1998-05

title: Civilisation, settlers and wanderers: Law, politics and mobility in nineteenth century New Zealand and Australia

authors: Seuffert, Nan

subjects: colonization

abstract: Mobility was constitutive of the 19th century British colonial period in the Pacific. The circulation of capital and commodities, technologies of transportation and communication, travelling ideologies and systems of governance and surveillance, as well as the movement of explorers, whalers, labourers, settlers, missionaries, colonial administrators, convicts, soldiers, sojourners, immigrants, and transnational and displaced indigenous peoples, all shaped the politics and the period (see Ballantyne 2009: 7-8; Seuffert 2006: 7-8; Arrighi 1994: 48-58). Highly mobile British and European immigrants with money or skills were termed 'settlers', with associated connotations of stabilising and civilising influences. Missionaries and colonial officials who were integral to colonisation were also often highly mobile, carrying policies and regulatory regimes with them, and their colonial roles as 'civilising' influences included 'settling' and advancing the position of indigenous and other colonised peoples. In contrast, the mobility of poor whites and racialised populations - such as 'Melanesian' indentured labourers (Banivanua-Mar 2007: 3-4)2, Indian workers, displaced indigenous peoples and 'sojourner' Chinese - attracted the attention of law (and policy) makers and institutional authorities and were subjected to various forms of surveillance, regulation and policing designed to constrain and contain them.

text: Civilisation, settlers and wanderers: Law, politics and mobility in nineteenth century New Zealand and Australia Mobility was constitutive of the 19th century British colonial period in the Pacific. The circulation of capital and commodities, technologies of transportation and communication, travelling ideologies and systems of governance and surveillance, as well as the movement of explorers, whalers, labourers, settlers, missionaries, colonial administrators, convicts, soldiers, sojourners, immigrants, and transnational and displaced indigenous peoples, all shaped the politics and the period (see Ballantyne 2009: 7-8; Seuffert 2006: 7-8; Arrighi 1994: 48-58). Highly mobile British and European immigrants with money or skills were termed 'settlers', with associated connotations of stabilising and civilising influences. Missionaries and colonial officials who were integral to colonisation were also often highly mobile, carrying policies and regulatory regimes with them, and their colonial roles as 'civilising' influences included 'settling' and advancing the position of indigenous and other colonised peoples. In contrast, the mobility of poor whites and racialised populations - such as 'Melanesian' indentured labourers (Banivanua-Mar 2007: 3-4)2, Indian workers, displaced indigenous peoples and 'sojourner' Chinese - attracted the attention of law (and policy) makers and institutional authorities and were subjected to various forms of surveillance, regulation and policing designed to constrain and contain them.

year: 2011