A comparison of the vocational training system of Britain and West Germany as experienced by minimum-age school leavers.

The sectoral and occupational structure of Britain and West Germany has increasingly changed over the last fifty years from a manual manufacturing based to a non-manual service sector based one. There has been a trend towards more managerial and less menial type occupations. Britain employs a higher proportion of its population in the service sector than in manufacturing compared to West Germany, except in retailing, where West Germany employs twice as many people as Britain. This is a stable sector of the economy in terms of employment, but the requirements of the workforce have changed in line with changes in the industry in both countries. School leavers in the two countries, faced with the same options (FE, training schemes or employment) have opted for the various options in different proportions: young Germans are staying longer in education before embarking on training and young Britons are now less likely to go straight into employment than ten years ago. Training is becoming more accepted as the normal route into employment with government policy leading the way, but public opinion still slow to respond. This study investigates how vocational training has adapted to the changing requirements of industry, often determined by technological advancements. In some areas e.g. manufacturing industry the changes have been radical, in others such as retailing they have not, but skill requirements, not necessarily influenced by technology have changed. Social-communicative skills, frequently not even considered skills and therefore not included in training are coming to the forefront. Vocational training has adapted differently in the two countries: in West Germany on the basis of an established over-defined system and in Britain on the basis of an out-dated ill-defined and almost non-existent system. In retailing German school leavers opt for two or three year apprenticeships whereas British school leavers are offered employment with or without formalised training. The publicly held view of the occupation of sales assistant is one of low-level skill, low intellectual demands and a job anyone can do. The traditional skills - product knowledge, selling and social-communicative skills have steadily been eroded. In the last five years retailers have recognised that a return to customer service, utilising the traditional skills was going to be needed of their staff to remain competitive. This requires training. The German retail training system responded by adapting its training regulations in a long consultative process, whereas the British experimented with YTS, a formalised training scheme nationwide being a new departure. The thesis evaluates the changes in these regulations. The case studies in four retail outlets demonstrate that it is indeed product knowledge and selling and social-communicative skills which are fundamental to being a successful and content sales assistant in either country. When the skills are recognised and taught well and systematically the foundations for career development in retailing are laid in a labour market which is continually looking for better qualified workers. Training, when planned and conducted professionally is appreciated by staff and customers and of benefit to the company. In retailing not enough systematic training, to recognisable standards is carried out in Britain, whereas in West Germany the training system is nevertheless better prepared to show innovative potential as a structure and is in place on which to build. In Britain the reputation of the individual company has a greater role to play, not ensuring a national provision of good training in retailing.

On waveform analysis, the adaptive task technique, and the effect of vibration on manual control skill

A re-examination of fundamental concepts and a formal structuring of the waveform analysis problem is presented in Part I. eg. the nature of frequency is examined and a novel alternative to the classical methods of detection proposed and implemented which has the advantage of speed and independence from amplitude. Waveform analysis provides the link between Parts I and II. Part II is devoted to Human Factors and the Adaptive Task Technique. The Historical, Technical and Intellectual development of the technique is traced in a review which examines the evidence of its advantages relative to non-adaptive fixed task methods of training, skill assessment and man-machine optimisation. A second review examines research evidence on the effect of vibration on manual control ability. Findings are presented in terms of percentage increment or decrement in performance relative to performance without vibration in the range 0-0.6Rms'g'. Primary task performance was found to vary by as much as 90% between tasks at the same Rms'g'. Differences in task difficulty accounted for this difference. Within tasks vibration-added-difficulty accounted for the effects of vibration intensity. Secondary tasks were found to be largely insensitive to vibration except secondaries which involved fine manual adjustment of minor controls. Three experiments are reported next in which an adaptive technique was used to measure the % task difficulty added by vertical random and sinusoidal vibration to a 'Critical Compensatory Tracking task. At vibration intensities between 0 - 0.09 Rms 'g' it was found that random vibration added (24.5 x Rms'g')/7.4 x 100% to the difficulty of the control task. An equivalence relationship between Random and Sinusoidal vibration effects was established based upon added task difficulty. Waveform Analyses which were applied to the experimental data served to validate Phase Plane analysis and uncovered the development of a control and possibly a vibration isolation strategy. The submission ends with an appraisal of subjects mentioned in the thesis title.

Self-training from labeled features for sentiment analysis

Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon with preferences on expectations of sentiment labels of those lexicon words being expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie-review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than existing weakly-supervised sentiment classification methods despite using no labeled documents.