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Provides a comprehensive, critical review of failure prediction with cash flow information since Beaver (1966); and tabulates the methods and cash flow variables used, and the results produced. Describes the literature as “inconsistent and inconclusive” and discusses possible reasons why, e.g. the measurement and diversity of cash flows, lack of model validation, multicollinearity etc. Points out the importance of cash to solvency and dividend payouts; and the limitations it places on creative accounting. Summarizes the reasons for previous inconsistencies and considers possibilities for further research.

To explain how cumulative efforts contribute to learning and literacy development.

A representation of how efforts lead to lasting growth is discussed through a variety of historical and current perspectives across content disciplines. This chapter includes depictions of how positive experiences can promote further success and recognizing one’s cumulative efforts and the effects from those are fundamental to educational attainment.

The value one places on tasks such as reading or writing is often aligned to the frequency with which those events occur. Students view their time and effort as capital; they are students’ most valued possessions, and how they allocate these commodities is a choice.

For students to become avid readers and writers, we must utilize a host of strategies to impress the notion that these activities are worth their attention, time, and investment.

This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.

This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.

There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.

The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.

A number of major studies of social stratification have been conducted since the Second World War. Focusing on societal openness, or equality of opportunity, these studies have ranged from investigations of individual status attainment and mobility processes to the analysis of class closure and class conflict among groups. What these studies have mostly in common, however, is that the form of stratification within which mobility or class closure is considered is occupational. Also, they have almost entirely concentrated on the male population. Openness, or equality of opportunity, is usually assessed in terms of the association between fathers' and sons' occupations, or the relative chances a son has to inherit his father's class or status position (Dale et al, 1985). Low rates of inheritance, or a lack of association in class position across generations, are interpreted as indicating weak tendencies towards social closure between strata and classes. Strong associations, or low rates of class interchange, are taken as evidence of greater structuration.

PRESIDENT: F. C. Francis, M.A., F.S.A., British Museum. PAST PRESIDENTS SERVING ON COUNCIL: Dr. Barbara Wootton, University of London; Sir Raymond Streat, K.B.E., Cotton Board. VICE‐PRESIDENTS: Sir Andrew McCance, Colvilles Ltd.; Sir Alexander Todd, Cambridge University; Sir Ben Lockspeiser, K.C.B., Tube Investments Ltd.; Sir Wavell Wakefield, M.P. HONORARY TREASURER: J. E. Wright, Institution of Electrical Engineers. HONORARY SECRETARY: Mrs. Joyce Lancaster‐Jones, British Council.

Social mobility has long been viewed as an integrative mechanism for societies. For example, whereas earlier American researchers saw opportunities for social mobility as a vital factor in promoting political stability and the maximisation of equality of opportunity, more recent British sociologists have noted the role of social mobility in legitimising inequalities and impeding class formation and class action. Despite this stress on the importance of social mobility for societal stability, however, there has been little sustained empirical study of the influence of marital homogany either in terms of societal integration or the reproduction of class relations. Yet, as Jones (1987) notes, this neglect of the issue is somewhat puzzling. Not only have earlier studies of class phenomena such as Sorokin (1927) and Schumpeter (1951) paid considerable attention to marriage and the family in relation to social stability, class formation and class cohesion, but, marital patterns, in terms of the economic and social resources of parents, are consistently emphasised as one vital factor in accounting for the subsequent occupational achievements of children (Hayes and Miller, 1991; Miller and Hayes, 1990; Abbott and Sapsford, 1987; Boyd, 1985; Dale et.al., 1985; Cooney et.al., 1982; Marini, 1980) and the political attitudes of households in general (Leiulfsrud and Woodward, 1988, 1987; Abbott, 1987; Britten, 1984).

SEPTEMBER sees most librarians again at the daily round, although some, including those of the universities and schools, are still scattered on mountains, golf‐courses, beaches and oceans for a short while yet. To older men there is a curious feeling aroused by the knowledge that there is no Library Association Conference this month. They may, in a measure, find compensation in attending the annual meeting of the London and Home Counties Branch of the Association, which will be at St. Albans, or that of A.S.L.I.B., which has Gonville and Caius College, Cambridge, as its venue. Both, by some lack of care which might have been avoided, occur on the same week‐end, September 24–26. Quite clearly the special problems of librarianship technique, such as processes, book‐selection and purchase, classification, catalogues, fines, publicity, salaries, hours, and so on almost infinitely, can no longer be discussed profitably at the Annual Meeting of the Library Association; smaller gatherings, such as these, are their fitting place. We make a suggestion to the L.A. Council, for what it is worth and without pretence to being original. It is that it should indicate to all its branches and sections the main questions to which they should devote attention, and that in due course they should produce their conclusions on them. These, being pooled, would form the basis of the L.A. Annual Meeting. This would make a purposeful programme for all, and the results of the Conference might then be considered definite and practical.

Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show the usage of this information in financial decision processes.

Need for the Study: Main financial reports such as balance sheets and income statements can be analysed by statistical methods. However, an expanded financial reporting framework needs new analysing methods due to unstructured and big data. The study offers a solution to the analysis problem that comes with non-financial reporting, which is an essential communication tool in corporate reporting.

Methodology: Text mining analysis of annual reports is conducted using software named R. To simplify the problem, we try to predict the companies’ corporate governance qualifications using text mining. K Nearest Neighbor, Naive Bayes and Decision Tree machine learning algorithms were used.

Findings: Our analysis illustrates that K Nearest Neighbor has classified the highest number of correct classifications by 85%, compared to 50% for the random walk. The empirical evidence suggests that text mining can be used by all stakeholders as a financial analysis method.

Practical Implications: Combining financial statement analyses with financial reporting analyses will decrease the information asymmetry between the company and stakeholders. So stakeholders can make more accurate decisions. Analysis of non-financial data with text mining will provide a decisive competitive advantage, especially for investors to make the right decisions. This method will lead to allocating scarce resources more effectively. Another contribution of the study is that stakeholders can predict the corporate governance qualification of the company from the annual reports even if it does not include in the Corporate Governance Index (CGI).