Browsing by Author "Kornik, Saul"
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- ItemOpen AccessMachine learning for corporate failure prediction : an empirical study of South African companies(2004) Kornik, Saul; Everingham, Geoff; Greene, JohnThe research objective of this study was to construct an empirical model for the prediction of corporate failure in South Africa through the application of machine learning techniques using information generally available to investors. The study began with a thorough review of the corporate failure literature, breaking the process of prediction model construction into the following steps: * Defining corporate failure * Sample selection * Feature selection * Data pre-processing * Feature Subset Selection * Classifier construction * Model evaluation These steps were applied to the construction of a model, using a sample of failed companies that were listed on the JSE Securities Exchange between 1 January 1996 and 30 June 2003. A paired sample of non-failed companies was selected. Pairing was performed on the basis of year of failure, industry and asset size (total assets per the company financial statements excluding intangible assets). A minimum of two years and a maximum of three years of financial data were collated for each company. Such data was mainly sourced from BFA McGregor RAID Station, although the BFA McGregor Handbook and JSE Handbook were also consulted for certain data items. A total of 75 financial and non-financial ratios were calculated for each year of data collected for every company in the final sample. Two databases of ratios were created - one for all companies with at least two years of data and another for those companies with three years of data. Missing and undefined data items were rectified before all the ratios were normalised. The set of normalised values was then imported into MatLab Version 6 and input into a Population-Based Incremental Learning (PBIL) algorithm. PBIL was then used to identify those subsets of features that best separated the failed and non-failed data clusters for a one, two and three year forward forecast period. Thornton's Separability Index (SI) was used to evaluate the degree of separation achieved by each feature subset.
- ItemOpen AccessPlacement, support, and retention of health professionals: national, cross-sectional findings from medical and dental community service officers in South Africa(BioMed Central, 2014-02-26) Hatcher, Abigail M; Onah, Michael; Kornik, Saul; Peacocke, Julia; Reid, StephenBackground: In South Africa, community service following medical training serves as a mechanism for equitable distribution of health professionals and their professional development. Community service officers are required to contribute a year towards serving in a public health facility while receiving supervision and remuneration. Although the South African community service programme has been in effect since 1998, little is known about how placement and practical support occur, or how community service may impact future retention of health professionals. Methods: National, cross-sectional data were collected from community service officers who served during 2009 using a structured self-report questionnaire. A Supervision Satisfaction Scale (SSS) was created by summing scores of five questions rated on a three-point Likert scale (orientation, clinical advising, ongoing mentorship, accessibility of clinic leadership, and handling of community service officers’ concerns). Research endpoints were guided by community service programmatic goals and analysed as dichotomous outcomes. Bivariate and multivariate logistical regressions were conducted using Stata 12. Results: The sample population comprised 685 doctors and dentists (response rate 44%). Rural placement was more likely among unmarried, male, and black practitioners. Rates of self-reported professional development were high (470 out of 539 responses; 87%). Participants with higher scores on the SSS were more likely to report professional development. Although few participants planned to continue work in rural, underserved communities (n = 171 out of 657 responses, 25%), those serving in a rural facility during the community service year had higher intentions of continuing rural work. Those reporting professional development during the community service year were twice as likely to report intentions to remain in rural, underserved communities. Conclusions: Despite challenges in equitable distribution of practitioners, participant satisfaction with the compulsory community service programme appears to be high among those who responded to a 2009 questionnaire. These data offer a starting point for designing programmes and policies that better meet the health needs of the South African population through more appropriate human resource management. An emphasis on professional development and supervision is crucial if South Africa is to build practitioner skills, equitably distribute health professionals, and retain the medical workforce in rural, underserved areas.