Position classification systems are formal methods for determining the relative worth of positions in an organization. The Office of Personnel Management (OPM) has responsibility and authority for federal position classification, except for certain positions in agencies exempted by law. OPM develops and issues classification standards and policies for the federal personnel system. Federal agencies then use these standards and policies to assign grades to positions. The General Schedule (GS) is a 15-grade pay system that covers 442 white-collar occupations and approximately 1.5 million full-time permanent employees in the federal white-collar workforce. Agencies classify most of these positions using either narrative or FES point-factor classification standards. The FES primary standard serves as the framework for individual classification standards written for each occupation. When we began our study, FES standards were in effect for 77 occupations covering approximately 441,000 full-time permanent nonsupervisory employees. Under FES, positions are assigned grades on the basis of the duties, responsibilities, and the qualifications required in terms of the following nine factors: knowledge required by the position includes the skills needed to apply supervisory controls entail the control exercised by the incumbent’s supervisor (not the incumbent’s span of control over subordinates); guidelines provide reference data or impose certain constraints on the incumbent’s use of knowledge; include desk manuals, established procedures and policies, traditional practices, and materials such as dictionaries, etc. ; and vary by specificity, applicability, and availability; complexity consists of the nature, variety, and intricacy of tasks and the difficulty and originality involved in performing the work; scope and effect encompass the relationship between the breadth and depth of the work and the effect of work products and services within and outside the organization; personal contacts refer to contacts with persons not in the supervisory purpose of contacts ranges from factual exchanges of information to situations involving significant or controversial issues and differing viewpoints, goals, or objectives; physical demands include physical characteristics such as agility, dexterity, and physical exertion—such as climbing, lifting, pushing, etc. ; and work environment pertains to the risks and discomforts in the employee’s physical surroundings or work assigned. As shown in table 1, each factor is broken down into graduated levels. Factors are composed of from three to nine levels with most having four to six levels. One factor—knowledge required by the position—has the largest range of points, from 50 for level 1 to 1,850 for level 9. To determine a position’s GS grade, the agency typically compares either the position description or information gathered through a “desk audit” with the nine FES factors described in the classification standard. After all nine factors are evaluated, the points for all factors are totaled, and the total for each position is converted to a GS grade by using a conversion table (see table 2). A contractor, with our supervision, developed a job content questionnaire on the basis of the FES primary standard. The contractor distributed it to a stratified random sample of 2,060 pairs of incumbents and their supervisors and received responses from 1,639 incumbent/supervisor pairs, which represents an overall response rate of about 80 percent. Because individual federal positions are classified through labor-intensive desk audits, it was not practical for us to study the majority of FES occupations using traditional classification methods. The contractor did, however, do desk audits of 78 judgmentally selected positions and compared the audit results with the related questionnaire responses. These comparisons indicated a fairly high correlation across occupations. The validity coefficient between the GS grades resulting from the desk audits and those from the questionnaires was .80 when the incumbent and supervisor questionnaire responses were averaged. We considered this correlation to be sufficiently high to validate the use of the job content questionnaire results for comparing groups of occupations.However, we cannot attest to the questionnaire’s validity when used across GS grades within occupations, for specific occupations, or for individual positions. Further, our study was not designed to determine whether, and if so why, the job content reflected by the questionnaires differed from that contained in the official job descriptions, which are the bases for the actual GS grades. We used an OPM database to identify a representative segment of incumbents and their supervisors in occupations with high, medium, or low representations of women or minorities. We defined occupations with high, medium, and low female representation as those in which women represented 70 percent or more, 31 to 69 percent, and 30 percent or less of incumbents, respectively. We considered occupations in which minorities represented more than 41 percent, 23 to 41 percent, or less than 23 percent of incumbents as those with high, medium, and low minority representation, respectively. Examples of occupations with high female representation included secretary, dental hygienist, medical clerk, dental assistant, and occupational therapist. Examples of occupations with high minority representation included border patrol agent and computer and equal employment opportunity specialists. We selected our sample of incumbents and their supervisors from a total of 58 occupations, which collectively represented about 90 percent of the full-time permanent nonsupervisory employees covered by FES when we designed our study. Because preliminary analyses indicated that more variation in undergrading and overgrading existed among occupations with similar gender and minority representation than between groups of occupations with different gender and minority representations, we did our analyses on the 37 occupations for which we had received completed questionnaires from at least 10 or more incumbent/supervisor pairs, for a total of 1,358 pairs or positions. These 37 occupations represented almost one-quarter of the federal white-collar workforce, or about 79 percent of the employees covered by FES, and the results of our study are generalizable only to this population. On the basis of the average total factor level points derived from the questionnaires completed by the incumbent and the supervisor, we determined the GS grade for each position using the FES conversion table (see table 2). We compared the questionnaire grade with the incumbent’s actual GS grade and considered the position to be aptly, or appropriately, graded if the questionnaire grade and the actual grade were the same. Otherwise, we considered positions to be overgraded if the actual grade was higher than the questionnaire grade and undergraded if the actual grade was lower than the questionnaire grade. Our study was not designed to permit us to approximate the number of positions that appeared to be overgraded, undergraded, or aptly graded for the portion of the federal workforce to which the results of our study are generalizable; identify the causes of any overgrading or undergrading resulting from either (1) our use of the primary rather than the occupation-specific classification standards, (2) the agencies’ application of classification standards to individual positions, or (3) management decisions regarding the work incumbents were actually assigned versus their job descriptions; determine whether any difference on the basis of gender or minority status was inherent in the design of FES, as a product either of the factors that constitute FES or the allocation of weight or the point range assigned to each factor; or calculate what pay adjustments, if any, should be made. Appendix I contains a more detailed discussion of the job content questionnaire development and validation, sample selection, and response rate calculation. To determine the effects of female or minority representation on relative overgrading and undergrading, we used odds and odds ratios. We calculated the odds of occupations being undergraded rather than aptly graded by dividing the number of positions undergraded by the number aptly graded for groups of occupations. To determine how much more likely one group of occupations was to be undergraded than another group, we divided the odds of being undergraded for one group of occupations by the odds for the other group to form an odds ratio. We used the same procedures for overgrading. We used loglinear analysis to determine how the odds of occupations being overgraded or undergraded versus aptly graded varied (1) across the range of GS grades and (2) when the female or minority representation of the occupation was high, medium, or low. The strength of this particular statistical approach is that multiple variables can be analyzed simultaneously. Appendix II provides more detailed information on the calculation of odds and odds ratios and loglinear models tested and the results obtained. To gain historical perspective, we reviewed previous studies of federal classification issues. We also conferred with federal classification experts to obtain additional insights about possible explanations for specific findings. This study should not be referred to as a “pay equity” study because we examined only the relationship between job content and GS grades assigned through the use of FES and whether that relationship varied with the proportion of women or minorities in occupations. We obtained comments from OPM that are discussed on pages 11 through 12 and presented in appendix III. We did our study from January 1990 to September 1995 in accordance with generally accepted government auditing standards. To evaluate whether gender or minority representation had an effect on the variation between the actual grades and the questionnaire grades, we statistically eliminated the effect of the incumbents’ GS grades. Analysis of the remaining variation showed that occupations with high female representation were 1.77 times more likely to be undergraded rather than aptly graded compared with occupations having a low or medium female representation. Occupations with high minority representation were 2.18 times more likely to be overgraded rather than aptly graded compared with occupations having a low or medium minority representation. Classification experts with whom we consulted about our results and the available literature offered a few occupation-specific hypotheses about possible causes. For example, key occupations with high minority representation that appeared to be overgraded included (1) border patrol agents, (2) equal employment opportunity and compliance specialists, and (3) computer specialists. Previous studies of federal classification issues maintained that FES was ineffective for specialists such as law enforcement related occupations because physical demands and work environment are not highly valued FES factors but are considered significant in these occupations.