An examination of Lotka's law in the field of Library and Information Studies

The purpose of this study was to test Lotka’s law of scientific publication productivity using the methodology outlined by Pao (1985), in the field of Library and Information Studies (LIS). Lotka’s law has been sporadically tested in the field over the past 30+ years, but the results of these studies are inconclusive due to the varying methods employed by the researchers. ^ A data set of 1,856 citations that were found using the ISI Web of Knowledge databases were studied. The values of n and c were calculated to be 2.1 and 0.6418 (64.18%) respectively. The Kolmogorov-Smirnov (K-S) one sample goodness-of-fit test was conducted at the 0.10 level of significance. The Dmax value is 0.022758 and the calculated critical value is 0.026562. It was determined that the null hypothesis stating that there is no difference in the observed distribution of publications and the distribution obtained using Lotka’s and Pao’s procedure could not be rejected. ^ This study finds that literature in the field of Library and Information Studies does conform to Lotka’s law with reliable results. As result, Lotka’s law can be used in LIS as a standardized means of measuring author publication productivity which will lead to findings that are comparable on many levels (e.g., department, institution, national). Lotka’s law can be employed as an empirically proven analytical tool to establish publication productivity benchmarks for faculty and faculty librarians. Recommendations for further study include (a) exploring the characteristics of the high and low producers; (b) finding a way to successfully account for collaborative contributions in the formula; and, (c) a detailed study of institutional policies concerning publication productivity and its impact on the appointment, tenure and promotion process of academic librarians. ^

An Examination of Lotka’s law in the Field of Library and Information Studies

The purpose of this study was to test Lotka’s law of scientific publication productivity using the methodology outlined by Pao (1985), in the field of Library and Information Studies (LIS). Lotka’s law has been sporadically tested in the field over the past 30+ years, but the results of these studies are inconclusive due to the varying methods employed by the researchers. A data set of 1,856 citations that were found using the ISI Web of Knowledge databases were studied. The values of n and c were calculated to be 2.1 and 0.6418 (64.18%) respectively. The Kolmogorov-Smirnov (K-S) one sample goodness-of-fit test was conducted at the 0.10 level of significance. The Dmax value is 0.022758 and the calculated critical value is 0.026562. It was determined that the null hypothesis stating that there is no difference in the observed distribution of publications and the distribution obtained using Lotka’s and Pao’s procedure could not be rejected. This study finds that literature in the field of library and Information Studies does conform to Lotka’s law with reliable results. As result, Lotka’s law can be used in LIS as a standardized means of measuring author publication productivity which will lead to findings that are comparable on many levels (e.g., department, institution, national). Lotka’s law can be employed as an empirically proven analytical tool to establish publication productivity benchmarks for faculty and faculty librarians. Recommendations for further study include (a) exploring the characteristics of the high and low producers; (b) finding a way to successfully account for collaborative contributions in the formula; and, (c) a detailed study of institutional policies concerning publication productivity and its impact on the appointment, tenure and promotion process of academic librarians.

Improving the scientific reliability of biological detection of explosives by Canis familiaris: Active odour signatures and their implications

The use of canines as a method of detection of explosives is well established worldwide and those applying this technology range from police forces and law enforcement to humanitarian agencies in the developing world. Despite the recent surge in publication of novel instrumental sensors for explosives detection, canines are still regarded by many to be the most effective real-time field method of explosives detection. However, unlike instrumental methods, currently it is difficult to determine detection levels, perform calibration of the canines' ability or produce scientifically valid quality control checks. Accordingly, amongst increasingly strict requirements regarding forensic evidence admission such as Frye and Daubert, there is a need for better scientific understanding of the process of canine detection. ^ When translated to the field of canine detection, just like any instrumental technique, peer reviewed publication of the reliability, success and error rates, is required for admissibility. Commonly training is focussed towards high explosives such as TNT and Composition 4, and the low explosives such as Black and Smokeless Powders are added often only for completeness. ^ Headspace analyses of explosive samples, performed by Solid Phase Microextraction (SPME) paired with Gas Chromatography - Mass Spectrometry (GC-MS), and Gas Chromatography - Electron Capture Detection (GC-ECD) was conducted, highlighting common odour chemicals. The odour chemicals detected were then presented to previously trained and certified explosives detection canines, and the activity/inactivity of the odour determined through field trials and experiments. ^ It was demonstrated that TNT and cast explosives share a common odour signature, and the same may be said for plasticized explosives such as Composition C-4 and Deta Sheet. Conversely, smokeless powders were demonstrated not to share common odours. An evaluation of the effectiveness of commercially available pseudo aids reported limited success. The implications of the explosive odour studies upon canine training then led to the development of novel inert training aids based upon the active odours determined. ^