Premium
A JOB SAMPLING APPROACH TO MERIT SYSTEM EXAMINING 1
Author(s) -
SCHWARTZ DONALD J.
Publication year - 1977
Publication title -
personnel psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.076
H-Index - 142
eISSN - 1744-6570
pISSN - 0031-5826
DOI - 10.1111/j.1744-6570.1977.tb02087.x
Subject(s) - schedule , construct (python library) , job performance , job analysis , task (project management) , identification (biology) , process (computing) , psychology , domain (mathematical analysis) , selection (genetic algorithm) , construct validity , rating scale , computer science , sampling (signal processing) , industrial engineering , social psychology , artificial intelligence , psychometrics , job satisfaction , systems engineering , engineering , mathematics , mathematical analysis , botany , developmental psychology , filter (signal processing) , computer vision , biology , programming language , operating system , clinical psychology
The application of content validity to a merit examining process or rating schedule requires an extension of the concept beyond that of work samples and tests of knowledges or skills to measures of ability and personal characteristics. A method for accomplishing this without violating the principles of content validity is presented. This technique, called the job sampling approach, is a task‐based, structured system of eliciting the information necessary to construct the rating schedule from sources most able to provide that information and for using the information to construct the rating schedule and linking it to job performance. The steps include: definition of the performance domain of the job in terms of process statements; identification of the selection and measurement objectives of the organization; development of the measurement domain in relation to the performance domain and to the selection and measurement objectives; and demonstration that a close match between the performance domain and the measurement domain was in fact achieved.