Document Set Differentiability Analyzer v. 0.1

Abstract

Software is a JMP Scripting Language (JSL) script designed to evaluate the differentiability of a set of documents that exhibit some conceptual commonalities but are expected to describe substantially different – thus differentiable – categories. The script imports the document set, a subset of which may be partitioned into an additions pool. The bulk of the documents form a basis pool. Text analysis is applied to the basis pool to extract a mathematical representation of its conceptual content, referred to as the document concept space. A bootstrapping approach is applied to that mathematical representation in order to generate a representation of a large population of randomly designed documents that could be written within the concept space, notably without actually writing the text of those documents.The Kolmogorov-Smirnov test is applied to determine whether the basis pool document set exhibits superior differentiation relative to the randomly designed virtual documents produced by bootstrapping. If an additions pool exists, the documents are incrementally added to the basis pool, choosing the best differentiated remaining document at each step. In this manner the impact of additional categories to overall document set differentiability may be assessed.The software was developed to assess the differentiability of job description document sets. Differentiability is key to meaningful categorization. Poor job differentiation may have economic, ethical, and/or legal implications for an organization. Job categories are used in the assignment of market-based salaries; consequently, poor differentiation of job duties may set the stage for legal challenges if very similar jobs pay differently depending on title, a circumstance that also invites economic waste.The software can be applied to ensure job description set differentiability, reducing legal, economic, and ethical risks to an organization and its people. The extraction of the conceptual space to a mathematical representation enables identification of exceedingly similar documents. In the event of redundancy, two jobs may be collapsed into one. If in the judgment of the subject matter experts the jobs are truly different, the conceptual similarities are highlighted, inviting inclusion of appropriate descriptive content to explicitly characterize those differences. When additional job categories may be needed as the organization changes, the software enables evaluation of proposed additions to ensure that the resulting document set remains adequately differentiated.