Nominal and ordinal data are two types of data categories. The difference between nominal and ordinal data lies primarily in the presentation of the data. Ordinal data is a numerical score that exists on a scale and is a numerical quantity of a particular value. Nominal data is a set of information organized by category or name. A nominal data set is also known as a categorical data set.
There is no indication of value within a nominal data set. The color red, for example, can be viewed in a number of different ways. Considering “safety” as a spectrum rather than a dichotomy is much like looking at the color red. Thinking of safety as nominal data implies that there is only safe or unsafe. But when looking at safety as ordinal data, you incorporate a spectrum of value that can imply varying degrees of safety.
Just as language has ambiguous tendencies, colors can as well. Colors are often used as nominal categories such as in the defense readiness condition (DEFCON) levels. Here colors are used as ordinal categories ranging from blue to white, with each level corresponding to a higher threat. Yet even this use of colors can fail to communicate the proper threat and subsequent response.
If a particular threat falls between levels on the color map, where would these threats be categorized? Having spectrum of color threats rather than more undefined blocked categories might be a better way to go. This could alleviate many ambiguities and allow for situations that may fall into the “gray area” as opposed to being “black and white.”
The importance of language -- what we say and how we say it -- can be further illustrated by the personal experience of former U.S. Marine, now social psychology student at the University of Louisiana (Monroe) Chad Lambert. Lambert was deployed to the Al Anbar Province of Iraq and the Helmand Province of Afghanistan in support of Operation Iraqi Freedom and Operation Enduring Freedom, respectively.
The mission in Iraq was to hold their Area of Operation (AO) and provide security to the local population as local security forces transitioned into a more dominant role. In Afghanistan, Lambert’s team was tasked with clearing the AO of hostile forces and securing a foot hole in an area that had no previous Coalition Forces presence. The level of security required for each of these missions, along with the individual security required in the day to day activity of his unit, was dependent upon the number of conditions in its Operational Risk Management and Operational Risk Assessment criteria.
Based upon Lambert’s experience, he understood that an individual -- or an organization -- could never be completely “safe”, nor was it ever defenseless. Lambert and his peers were constantly reminded about the dangers of complacency and were instructed to mindful of the next threat. Death was the ultimate penalty for any lapse in vigilance.
In their 1986 research on correlations titled “The Psychometrics of Everyday Life,” Kunda and Nisbett argued that accurate correlation estimates can only be achieved if two criteria are met: the subjects must be highly familiar with the data in question, and the data must be highly capable of being unitized and interpreted clearly. Without these two criteria being met the researchers found people were subject to “extreme inaccuracy” in the correlations they made.
In Lambert’s case, the communication was known and understood. This allowed him to correctly assess, compare and correlate his security level with general safety. He understood that “absolute safety” was not possible, but there were steps he could take to be smarter and become more safe or secure. Lambert realized that safety was a continuous variable rather than a dichotomous variable. He could never be truly safe, because the threats that existed were constantly evolving. Therefore, his security assessments had to constantly evolve to meet the ongoing threat. Lambert also understood that he was never without defense – whether or not they were adequate enough to stop the threat.
Morgan Sneed, a retired staff sergeant assigned to HQ PACAF as a combat correspondent during multiple deployments throughout Asia, also discovered that thinking in dichotomies or using absolutes like “safe” could actually be quite dangerous.