title: National Fitness or Failure? Heredity, Vice and Racial Decline in New Zealand Psychiatry: A Case Study of the Auckland Mental Hospital, 1868-99

authors: Dawson, Maree Elizabeth

subjects: history

abstract: This thesis examines anxieties about national fitness and efficiency in nineteenth-century New Zealand through a detailed study of medical and popular ideas about the causes of mental illness. In particular, it foregrounds the perceived roles played by heredity and vice in medical diagnoses both inside institutions and in wider discussions about mental illness. The thesis draws upon medical journals, popular newspaper articles, government reports and debates, and patient case notes from the Auckland Mental Hospital between 1868 and 1899 to investigate discourses about the mentally ill, and to highlight the relationships between anxieties about this ‘problem’ section of the population and contemporary social concerns. This methodology demonstrates how a range of texts helped to produce a discursive association between heredity and vice, mental illness, and a feared decline in the ‘fitness’ of the ‘British’ race in New Zealand and in the wider British World, and also that the mentally ill in nineteenth-century New Zealand were often depicted as living consequences of a family history of indulgence in various forms of vice, or of the procreation of the mentally unfit. Medical and popular ideas about general paralysis and puerperal insanity, in particular, were strongly related to gender and class norms, and throughout this thesis, ideals of class and gender are explored as shaping influences on medical and popular theories about the aetiology of mental illness in general.
By drawing on medical discourses from Britain and New Zealand, this thesis also demonstrates the transnational nature of psychiatric medical theories deployed in Britain and New Zealand. This transnational transmission of ideas occurred through the migration of British born and educated psychiatrists to New Zealand, the context of British medical journals (such as the British Medical Journal and the Journal of Mental Science) which circulated in New Zealand, and attendance at Intercolonial Medical Congresses, shared between New Zealand and the Australian colonies from 1892. Transactions from these congresses, along with medical journal articles and popular sources, reveal that the period from 1868 until the end of the nineteenth century was an intellectual environment ripe for the emergence of concerns about racial decline, a trend highlighted by the presence of the mentally ill, in a ‘new’ society.

text: National Fitness or Failure? Heredity, Vice and Racial Decline in New Zealand Psychiatry: A Case Study of the Auckland Mental Hospital, 1868-99 This thesis examines anxieties about national fitness and efficiency in nineteenth-century New Zealand through a detailed study of medical and popular ideas about the causes of mental illness. In particular, it foregrounds the perceived roles played by heredity and vice in medical diagnoses both inside institutions and in wider discussions about mental illness. The thesis draws upon medical journals, popular newspaper articles, government reports and debates, and patient case notes from the Auckland Mental Hospital between 1868 and 1899 to investigate discourses about the mentally ill, and to highlight the relationships between anxieties about this ‘problem’ section of the population and contemporary social concerns. This methodology demonstrates how a range of texts helped to produce a discursive association between heredity and vice, mental illness, and a feared decline in the ‘fitness’ of the ‘British’ race in New Zealand and in the wider British World, and also that the mentally ill in nineteenth-century New Zealand were often depicted as living consequences of a family history of indulgence in various forms of vice, or of the procreation of the mentally unfit. Medical and popular ideas about general paralysis and puerperal insanity, in particular, were strongly related to gender and class norms, and throughout this thesis, ideals of class and gender are explored as shaping influences on medical and popular theories about the aetiology of mental illness in general.
By drawing on medical discourses from Britain and New Zealand, this thesis also demonstrates the transnational nature of psychiatric medical theories deployed in Britain and New Zealand. This transnational transmission of ideas occurred through the migration of British born and educated psychiatrists to New Zealand, the context of British medical journals (such as the British Medical Journal and the Journal of Mental Science) which circulated in New Zealand, and attendance at Intercolonial Medical Congresses, shared between New Zealand and the Australian colonies from 1892. Transactions from these congresses, along with medical journal articles and popular sources, reveal that the period from 1868 until the end of the nineteenth century was an intellectual environment ripe for the emergence of concerns about racial decline, a trend highlighted by the presence of the mentally ill, in a ‘new’ society.

year: 2013

title: Learning from batched data: model combination vs data combination

authors: Ting, Kai Ming

subjects: computer science

abstract: When presented with multiple batches of data, one can either combine them into a single batch before applying a machine learning procedure or learn from each batch independently and combine the resulting models. The former procedure, data combination, is straightforward; this paper investigates the latter, model combination. Given an appropriate combination method, one might expect model combination to prove superior when the data in each batch was obtained under somewhat different conditions or when different learning algorithms were used on the batches. Empirical results show that model combination often outperforms data combination even when the batches are drawn randomly from a single source of data and the same learning method is used on each. Moreover, this is not just an artifact of one particular method of combining models: it occurs with several different combination methods. 
We relate this phenomenon to the learning curve of the classifiers being used. Early in the learning process when the learning curve is steep there is much to gain from data combination, but later when it becomes shallow there is less to gain and model combination achieves a greater reduction in variance and hence a lower error rate.
The practical implication of these results is that one should consider using model combination rather than data combination, especially when multiple batches of data for the same task are readily available. It is often superior even when the batches are drawn randomly from a single sample, and we expect its advantage to increase if genuine statistical differences between the batches exist.

text: Learning from batched data: model combination vs data combination When presented with multiple batches of data, one can either combine them into a single batch before applying a machine learning procedure or learn from each batch independently and combine the resulting models. The former procedure, data combination, is straightforward; this paper investigates the latter, model combination. Given an appropriate combination method, one might expect model combination to prove superior when the data in each batch was obtained under somewhat different conditions or when different learning algorithms were used on the batches. Empirical results show that model combination often outperforms data combination even when the batches are drawn randomly from a single source of data and the same learning method is used on each. Moreover, this is not just an artifact of one particular method of combining models: it occurs with several different combination methods. 
We relate this phenomenon to the learning curve of the classifiers being used. Early in the learning process when the learning curve is steep there is much to gain from data combination, but later when it becomes shallow there is less to gain and model combination achieves a greater reduction in variance and hence a lower error rate.
The practical implication of these results is that one should consider using model combination rather than data combination, especially when multiple batches of data for the same task are readily available. It is often superior even when the batches are drawn randomly from a single sample, and we expect its advantage to increase if genuine statistical differences between the batches exist.

year: 1997-05

title: How Maui captured the sun: using a MUD for educational simulation

authors: Cunningham, Sally Jo

subjects: computer science

abstract: MUDs (Multi-User Dungeons) are text-based, multi-user communication and modelling programs. This paper investigates the potential of a popular extensible MUD, the LambdaMOO system, as a tool for second language training and for educational simulation gaming.

text: How Maui captured the sun: using a MUD for educational simulation MUDs (Multi-User Dungeons) are text-based, multi-user communication and modelling programs. This paper investigates the potential of a popular extensible MUD, the LambdaMOO system, as a tool for second language training and for educational simulation gaming.

year: 1995-12