The Faculty Scholarly Productivity Index, a product of Academic Analytics, is a metric designed to create benchmark standards for the measurement of academic and scholarly quality within and among United Statesresearch universities. The index is based on a set of statistical algorithms developed by Lawrence B. Martin and Anthony Olejniczak. It measures the annual amount and impact of faculty scholarly work in several areas, including:
The FSPI analysis creates, by academic field of study, a statistical score and a ranking based on the cumulative scoring of a program's faculty using these quantitative measures compared against national standards within the particular discipline. Individual program scores can then be combined to demonstrate the quality of the scholarly work of the entire university. This information is gathered for over 230,000 faculty members representing 118 academic disciplines in roughly 7,300 Ph.D. programs throughout more than 350 universities in the United States.
The system for evaluating university programs that forms the basis of the FSPI was developed by Lawrence Martin and Anthony Olejniczak of Stony Brook University. Martin had been studying, speaking, and writing about faculty scholarly productivity since 1995. During that period, a series of discipline-specific, per-capita regression models was created and tested to evaluate their accuracy and the feasibility of predicting the academic reputation of the faculty of doctoral programs. These prototype materials employed data from the National Research Council's 1995 publication Continuity and Change, describing and evaluating American Ph.D. programs by field. Martin and Olejniczak found that the reputation of a program could be predicted well using a discipline-specific regression equation derived from quantitative, per capita data available for each program. Reputation could be predicted with high statistical significance but important deviations from the regression line were also apparent; that is to say, some schools were outperforming their reputation, while others were under-performing. The prototype materials based on this method, and the data from the 1995 NRC study, were subsequently presented at numerous academic conferences from 1996 to 2004, and have formed the basis on which the FSP Index was developed. Unfortunately, like many academic productivity algorithms, the FSPI is not without major flaws. It fails to adequately differentiate among and apply appropriate measures to evaluating the very distinct academic fields represented in most colleges and universities. Furthermore, a number of specific objections have been raised about how the FSPI measures scholarly productivity. Among them are: 1) inadequate—or inconsistent—weighting of quality of journals in which publications appear; 2) failure to differentiate labor involved in producing different types of publications citation indexes, extensively used in scholarly productivity indexes, do not measure citations in books; 5) citation indexes are more appropriate for hard science disciplines and less appropriate for humanities disciplines; 6) non-conventional publications, which are increasing in number use of such indexes promotes "researching and publishing to the index" in order to preserve and enlarge university, government, and private grant support—and indirectly promote conservative, safe, mainstream research and publications. In spite of these objections, today the product is used by numerous universities.
