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Attempts at treatment and training in correctional institutions have historically preceded the establishment of adequate diagnosis and treatment-planning. Mass work and socialization programmes have generally been instituted in the more treatment-focused correctional systems, not with any realistic assurance that they could be adapted to the individual needs of inmates, but rather because such programmes were considered worthwhile, per se. On the North American continent, new attempts have been made in the past twenty-five years to apply to corrections the principle long-recognized in other treatment fields, i.e., individual diagnosis as the prerequisite to effective treatment. This study briefly reviews the development of correctional classification (diagnosis and treatment-planning) up to the present time, and describes the many penological trends evidenced by this development, in keeping with the various influences of the humanitarians and social scientists. It is suggested, perhaps unconventionally, that the correctional classification process is actually the final step in a series of more general "classifications" by the police, the community, and so forth. Four contemporary classification systems selected for their progressive features are described in detail: (a) the British "Borstal" system, (b) the State of New York, (c) the State of Pennsylvania, and (d) the State of California programmes. These programmes were selected from a wider survey, using the American Prison Association's Directory of Institutions and Manual of Correctional Standards as the criteria for selection. Classification practice within the British Columbia Provincial Gaol Service is next examined and compared with the other systems outlined, for the purposes of assessing the comprehensiveness of the local service and suggesting changes for its improvement. Contributions to classification theory and practice made by social work and related disciplines are evidenced throughout the enquiry. From the systems surveyed, it is apparent that certain features of administration and process are common to all effective classification programmes. Most of these could be incorporated, with appropriate modifications, into existing practice within the Provincial Gaol Service. The possibilities of this development are assessed in the concluding chapter. / Arts, Faculty of / Social Work, School of / Graduate

>Magister Scientiae - MSc / This research is on a comparative evaluation of 3D and spatio-temporal deep learning methods for crime classification and prediction using the Chicago crime dataset, which has 7.29 million records, collected from 2001 to 2020. In this study, crime classification experiments are carried out using two 3D deep learning algorithms, i.e., 3D Convolutional Neural Network and the 3D Residual Network. The crime classification models are evaluated using accuracy, F1 score, Area Under Receiver Operator Curve (AUROC), and Area Under Curve - Precision-Recall (AUCPR). The effectiveness of spatial grid resolutions on the performance of the classification models is also evaluated during training, validation and testing.