Just because meanings are translated into numbers and then statistics are employed on the numbers, does not by itself justify the procedure. Some psychologists eschew the practice of natural psychological science in the mould of positivism and naive realism. The problem occurs because methods of the natural sciences are taken as a model for measuring the meaning of objects in intersubjective milieus. Accordingly, the justification of the interpretative standpoint taken by human study feels the need to legitimate its practices through self-reflexivity and explain how its claims are acquired. But from the beginning, nothing in the sphere of the meaning of objects of attention that lie within complex ever-changing relationships could ever be considered a fact in terms of meaning outside of times, places, perspectives-taken and a whole range of other contributing considerations. In the world of meaning, how research questions are framed is causative in making the results claimed. And, that is one contributory reason as to why there are very many possible ways of the same meaningful object appearing. So whilst the same phenomenon of meaning may have some aspects of it that are conceptual pointing (due to them being expressed in speech or thoughts), then there are others that are nonverbally indicated (their referents are emotions felt, implicit connections to other objects, tacit never mentioned or explained contexts, or the whole situation refers to culture-bound processes within that culture’s commonsense). There is the hermeneutic reasoning required in idealising meaning in the way that eidetics does—but the same applies to all stances. Accordingly, the difference between the woman in the street and a pure psychologist with 20 years experience is that the latter is well-practised in their tradition; whereas the woman in the street just knows what she knows about meaning and mental processes.

Quantitative hypothesis-testing is the dominant model in natural psychological science. But there are many psychologists within the discipline who criticise this format for a variety of reasons. Within the community of mainstream psychologists, the statistician Jacob Cohen has referred to the use of basic logic and methodology by some colleagues as being “mesmerized by a single all-purpose mechanized ‘objective’ ritual in which we convert numbers into other numbers… we have come to neglect close scrutiny of where the numbers come from”, (Cohen 1990, 1310). Another mainstream psychologist, Paul Meehl, stated that “I am not making some nit-picking statisticians’ correction. I am saying that the whole business [of psychology] is so radically defective as to be scientifically pointless”, (1978, 26). The idea of testing hypotheses and using a null hypothesis does not prevent extraneous variables intruding. For consciousness continually learns and takes its learning with it, so the realisation is that “the empirical fact that everything is correlated with everything else, more or less”, (Meehl 1990, 123). If a hypothesis cannot be made, or cannot be tested empirically, then science as falsificationism cannot be pursued. If an outcome is a correlation that is not greater than chance, then the hypothesis must be discarded or the whole theory discarded.

Natural psychological science converts meaning into numbers to test its predictions that are generated from theory. It performs statistical operations and reinterprets the results back into meaning. In short, their view of their procedures is that quantitative research is the preferred experimental design because it enables the testing of predictions. But for pure psychology , quantitative design in natural psychological science is based on reificatory assumptions that justify an experimental tradition that cannot attend to the biopsychosocial in the full spectrum of its existence. Indeed, the tradition continues contrary to criticism in order to keep the idea that psychology is a science like other forms of natural science. But in fact, only small parts of psychology properly obey the idea of science where the investigation of natural being becomes standardised such as behavioural genetics. This is because identical twins who have grown up apart are studied as to how the influences of their enculturation form their personalities and aptitudes in comparison with each other. This means finding identical twins to understand contextual mental and physical differences.

Participants in empirical research can have their experiences and meanings interpreted in qualitative or quantitative ways. On the one hand, qualitative research looks for common meaningful themes and is made through an applied hermeneutics for classifying and coding the meanings expressed, about a specific event or a type of process between people. On the other hand, in quantitative research, a research question is answered by allocating numbers to the meaningful events and processes observed. The psychometric processes are ways of turning meaningful and observable behaviour, or other meaningful expressions of relating in a situation, into numbers that can be manipulated and stand for analogue meaningful processes of the experiences of the participants. Strictly speaking, psychometrics is turning the ‘analogue into the digital’ in the sense of allocating discrete numbers to what had been more wholistic and implicit contextual experience that was not reflected on (Wilden 1972). The psychometric process could start with self-rating questionnaires that turn experiences and meanings into standardised numerical scores, for instance, or that participants are rated by trained persons who are tested on the constancy of their interpretative skills with respect to a definitive manual to achieve “inter-rater reliability”. This format is acceptable if it has been tried and checked previously, or if the participants have been sufficiently schooled in how to rate themselves. The precise way in which meaning and experiences are numericised can be unclear, because some questionnaires are handed out without formal instruction to the participants in the research to explain how to rate themselves in a standardised manner. Clearly, some will over-rate and some will under-rate with respect to each other. The numbers created are analysed by statistical means to obtain a mathematical understanding of their significance, as a relationship between input and output, to see if there are correlations of occurrence or other trends between the parameters being observed.

What makes good experimental design is the repetition of the same test at two different times for the same group. This makes the group become its own control group, so that variations and idiosyncrasies in interpretative style and bias among the participants remains the same even if they do under- or over-rate themselves. The strength of this experimental design can be seen in comparison: poor experimental design features the use of two different groups who may be insufficiently similar with each other. In the latter case, one group gets the meaning-making process to be investigated: whilst the control group does not. This introduces a problematic factor into the experiment because it becomes a question as to what degree the groups are comparable and how all other variables in the intersubjective life can be controlled in addition to how well they are rated. It is the case that random events in a person’s life cannot be prevented and that external events will make their mark on the meanings being numericised. The reasoning behind the many ways of performing experimental psychology needs to be clear. The claim that something is a ‘scientific fact’ has to be scrutinised in order to reveal its meaning-making processes. For instance, the use of statistics should not hide potentially erroneous methodological design. Whereas good experimental design takes a sufficiently homogenous group of persons and applies psychometric tests to their meaningful experiences at two different times.