Normativity
Introduction
With assessment techniques, normativity refers to the ability of the technique to compare an individual's results to a larger population. Since the word normative sometimes implies specific rules to follow, it’s important to note that “normativity” in assessment only pertains to how data is normalized, eventually using a normal Gaussian distribution, to allow meaningful comparisons with other data of the same category.
Clinical Use
Normative assessments usually compare people based on gender, culture, age, or job type. For example, some clinical assessments use different norms for men and women or for different age groups. Scales for adolescents differ from those for adults and seniors, which helps to improve treatment quality.
While this approach is necessary in clinical settings, it is not suitable for work applications because it may create inappropriate comparisons and bias by unfairly favoring one group over another.
As we know from research and are supported by GRI studies, behavioral factors are universal. Using a sample of people as diverse as possible—covering different genders, ages, political and religious beliefs, and cultural backgrounds—allows for comparisons based on a representative sample of the larger population.
The mean, or any other point on the scale, can serve as a reference for comparing measures. The mean is more neutral and practical, which is why we use it at GRI.
The standard deviation scale, or other scales such as decile scales, measures the distance from the reference point. We use the standard deviation scale at GRI because it provides a more accurate understanding of how much the measure deviates from the mean and represents the energy needed to do so.
In organizations, important comparisons are needed not only between individuals but also with the demands of their positions and teams. This requires analyzing people’s characteristics—which, in GRI’s case, are social behaviors—against comparable ones of the jobs and teams.
GRI Measures
The GRI measures combine the benefits of normative distributions and ipsativity, which helps analyze how different factors relate to each other. This is partly because of the survey's free-choice format, allowing respondents to select as many or as few adjectives as they like when answering the two questions. After scoring, the answers are compared to a larger population and ipsatized. Comparisons with jobs are possible through techniques such as the PBI, which assesses the behaviors expected in the role.