a strength, as Q is sometimes used with a single subject, and it makes research far less expensive. In such cases, a person will rank the same set of statements under different conditions of instruction. For example, someone might be given a set of statements about personality traits and then asked to rank them according to how well they describe herself, her ideal self, her father, her mother, etc. Working with a single individual is particularly relevant in the study of how an individual's rankings change over time and this was the first use of Q methodology. As Q methodology works with a small non-representative sample, conclusions are limited to those who participated in the study. In studies of intelligence, Q factor analysis can generate consensus based assessment (CBA) scores as direct measures. Alternatively, the unit of measurement of a person in this context is his factor loading for a Q-sort he or she performs. Factors represent norms with respect to schemata. The individual who gains the highest factor loading on an Operant factor is the person most able to conceive the norm for the factor. What the norm means is a matter, always, for conjecture and refutation (Popper). It may be indicative of the wisest solution, or the most responsible, the most important, or an optimized-balanced solution. These are all untested hypotheses that require future study. An alternative method that determines the similarity among subjects somewhat like Q methodology, as well as the cultural "truth" of the statements used in the test, is Cultural Consensus Theory. The "Q sort" data collection procedure is traditionally done using a paper template and the sample of statements or other stimuli printed on individual cards. However, there are also computer software applications for conducting online Q sorts. For example, UC Riverside's Riverside Situational Q-sort (RSQ), claims to measure the psychological properties of situations. Their International Situations Project is using the tool to explore the psychologically salient aspects of situations and how those aspects may differ across cultures with this university-developed web-based application. To date there has been no study of differences in sorts produced by use of computer based vs. physical sorting. One Q-sort should produce two sets of data. The first is the physical distribution of sorted objects. The second is either an ongoing 'think-out-loud' narrative or a discussion that immediately follows the sorting exercise. The purpose of these narratives were, in