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Systems-Orientated Research in Agriculture and Rural Development. Papers from an International Symposium, Montpellier, France, 21-25 November 1994. Edited under the direction of Michel Sebillotte. CIRAD-SAR, Montpellier, France, 1995, pp 1006. Price: not given. ISBN 2 87614 181 7. This vast book constitutes the proceedings of the International Symposium held in Montpellier in November 1994. There are about 200 papers and posters organised into 7 sections: methods, environment, high input agriculture, indigenous knowledge, local organisations, training and agricultural policy. About half of the contributions are in French; most of the rest are in English, with a few in Spanish. All papers have a summary in both French and English, while posters are reproduced in the language of origin only. The book comes with a 48-page supplement containing another 14 papers and posters that ‘came too late to be edited’, it says on the cover. The inside cover page of the main proceedings warns that the papers published are the sole responsibility of the authors, and that they were edited ‘... with no leeway to contact authors in the event of ambiguity.’ All this is fair warning. As a preface to this immense amount of material, the editor-in-chief writes an introduction of eight sentences, in which ‘... the need to rethink the methodological tools for analysis, diagnosis, and action’ is highlighted. I have not read all the English papers, let alone the French ones (life is too short and my French too mediocre), but a few comments might be made in trying to assess this book on a partial reading. First, the editing is not as bad as the warnings above might lead one to expect. There are some problems a few awful diagrams (some hand-drawn) and some grammatical and typographical errors, but by and large the editing is rather impressive. Second, as might be expected, there appears to be no agreement among the many authors as to what systems-orientated research actually is. It clearly means different things to different people. A ‘systems approach’ is not synonymous with Farming Systems Research, participatory research is not necessarily systems-related, and to my mind a fair proportion of the papers here couldn’t really be called systems papers at all, hard or soft. An inability to define the sphere of work probably does not matter much, but the reader should be aware that there is a enormous range of topics and methods in the book, presented under the general banner of ‘systems work’. Third, the absence of any index (apart from an author index and a listing of titles and authors) severely limits the usefulness of a book such as this. This is not a volume that lends itself to rapid look-up of information, and it left me wondering about its intended users. Fourth, even a cursory reading reveals the contrast between the North American and the European perspectives. There is rather little North American representation in the papers, perhaps symptomatic of a pervasive feeling
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among agricultural researchers in North America that FSR is yesterday’s bandwagon; whether this is a permanent or temporary state of affairs is hard to judge. But of course ‘systems work’ consists of a lot more than FSR, and the Europeans seem much more enthusiastic. There has been far too much concern with what FSR, and systems work in general, is and why it is different, and far too little on objective assessment of its efficacy. If your tools do not work, adapt them or find other tools that do. On the evidence of these proceedings, there is certainly a great deal of creativity going into systems work in Europe that is being applied all over the world, but on my limited reading there is a real dearth of assessment and documentation of impact. Call agricultural research whatever you like, but unless it is effective at solving real-world problems it is not of much use. Philip Thornton
Statistics for Business, Economics, and Management. Stephen R. Harrison and Rick H. U. Tamaschke. Prentice Hall Australia Pty Ltd., 1993, 733 pp. Price: not given (paperback). ISBN 0 7248 1112 5. As stated by the authors in the introduction, this book provides a broad introduction to statistical methods, and attempts to make the reader conversant with major aspects of quantitative analysis as applied to business, economics, and management. It is aimed at the application-orientated reader with a limited mathematics and statistics background. The book’s content is organized in what has become the usual way, proceeding with generalities on data types, descriptive statistics, and probability fundamentals through sampling theory, estimation, and hypothesis testing to linear regression and selected topics, which here include time series, index numbers, survey designs, analysis of variance, nonparametric methods and quality control and acceptance sampling. A database and detailed tables and figures are included to support examples and exercises. Chapters 1 to 13 cover the range of topics typically included in introductory and intermediate statistics books for business, economics and management. Chapter 14 to 18 cover more specialized topics of general application by science and engineering researchers. Explaining the fundamentals of statistical methods and statistical inference to those whose preparation starts and stops largely with algebra is a difficult endeavour at best, if not for the subtlety of the mathematics involved then simply by virtue of the formidable complexities of notation and computation which the subject presents to the reader. Two general methodological means to this end, distinct but certainly complementary, suggest themselves. One seeks to develop the reader’s statistical intuition, largely through verbalization