Conspiracy theory, Queerness and Science

Science is a central part of our life. Having largely replaced religious dogma, science allows us to know which direction to take in political and practical terms. The certainty of our words is therefore particularly important, since it will have a real impact on choices made by a large number of individuals who influence each other.

In general, when we think of science, we think of what is called ‘the hard sciences’. We can therefore imagine microscopes, tubes and other gadgets generally found in pharmaceutical laboratories. But science is actually a process. It is a way of thinking about our perceptions and our reasoning. Specifically, this means that one should be as open and aware as possible of the steps that led to a conclusion. By being aware of these steps, one can potentially replicate these results and ensure that they are not due to luck.

Similarly, the scientific process is the search for statements that are empirically true. This can be done through the analytical path, which involves finding a language that can describe and produce these true statements. And this process can then go through the synthetic path which checks whether these statements are found in reality, and to what extent. The question of measurement is important here since it underlies a fundamental principle: our statements cannot capture reality absolutely and perfectly. All we can do is approximate until we reach a functional level for specific goals.

Take, for example, the goal of going to the moon. Whether the moon is a satellite has little impact on going there. Specifically, its absolute ontological category is a function of our epistemological positioning, limited by human existence. On the other hand, knowing how close the moon is to what we associate a satellite with allows us to know what are the characteristics that enable us to act on it accordingly. Knowledge is therefore a question of degrees of association of concepts with each other, and with reality.

Back to our scientific sheep.

This association that we make of science with ‘hard’ sciences is in fact due to the difficulty of representing the scientific process visually (since a large part of our perception is visual, and therefore the basis of our categorizations) and that the representations which they do show us have less to do with anthropologists in urban areas as much as inventors-engineers dressed in white lab coats.

This association is made all the more powerful as the so-called hard sciences have been around longer than the “soft” sciences and have therefore had the opportunity to define the criteria of what represents the truth. This is, moreover, one of the major sources of biases that are difficult to root out in science. Science has long been defined by the groups in power, and our conception of it retains its traces. Their favorite tools have been elevated to necessary staples, and all other data has been relegated to bias. However, this is a mistake.

Science is not the panacea for mathematics. For a long time, moreover, the language of mathematics did not have as much rigor as it does now. It was the conscious work of mathematicians like David Hilbert and Bertrand Russel to systematize the different paradigms in order to be able to have a consistent language. It is this systematization that gives mathematics all its power. In short, if several minds are able to coordinate, the errors of some will be raised by the others, and it is more likely to arrive at a perception close to reality than if we are not able to communicate our thoughts.

Thus, the human sciences emerge with two difficulties in relation to this systematization:

First, the language of communication is not as systematic as the language of mathematics, since interlocutors can give words different meanings, and languages ​​are varied, sensitive to contexts and evolve over time.

Second, and this idea foreshadowed in the previous point, human intention is not accessible. Specifically, we cannot say for sure what is going on in the minds of other humans. Modern neuroscientific theories are making remarkable progress in this direction, but the semantic content of human thought and its impact on behavior are still relatively difficult to determine. We can therefore only infer possible representations and cognitive causes, based on partial, imperfect, incomplete observations.

We can also ask an individual to deliver his thoughts to us, but he can lie, or himself infer the content of his thought a posteriori to fulfill an expectation towards him. It is even possible that our thoughts, considered to be conscious, are in fact only inferences made by individuals to explain what is in fact a largely unconscious process for them, and which therefore has such potentially uncertain value.

How can we do social science under these conditions?

It is precisely through systematization and the multiplication of data that we can arrive at a result which minimizes uncertainties. Just as many individuals will minimize the degree of uncertainty and imprecision about their reality, social scientists expose their process to others to open it up to criticism, share their results for discussion and serve as blocks, in order to build a common language and knowledge. Some blocks are contradictory, because that is the nature of the process, but eventually the blocks that do not work in a knowledge building are discarded for blocks that work better. Specifically, a scientific edifice, often referred to as a paradigm, is generally used to make predictions (related to future actions). If certain blocks cause the predictions to be worse, and therefore lead to actions that do not lead us to our goals, these blocks are discarded, and replaced by blocks that strengthen the entire structure.

Sometimes the paradigm does not advance any more, and does not allow any more new predictions. Not all paradigms are necessarily perfect. Indeed, our history is strewn with shifting paradigms, rising from the ashes of those who came before them. When paradigms are near the end of their life, some blocks are maintained, and others must be rebuilt.

Thus, social science gradually equips itself with blocks that have passed the test of time, and increments in precision as they become accepted and verified findings (understand here that many different people with their positions agree on its predictability). Past contradictions are ironed out, and new contradictions emerge. This process continues, but still seems to be moving forward, allowing a generally deeper understanding of complex phenomena.

Social science is therefore endowed with the same scientific process as the ‘hard ’ sciences, and systematizes its language through paradigmatic progress. What’s more, the social sciences can handle a large number of different types of data. This data is translated into models, and predictions are produced from these models. It is through this approach that one can convey the essence of a type of knowledge, regardless of the type of data. The remaining problem is therefore the transfer of this data into a model. What happens so that this data is transformed into a model?

Researchers have a central role to play in this passage. Like any process, it has its share of interpretation.

The interpretation can seem contradictory to a systematized phenomenon, and is potentially biased, since the researcher has an interest anchored in his/her own position, and has potentially also invested a type of paradigm, which is now part of his or her identity. This is where the role of the exposure comes in. Researchers must express their position in the world, their interests and their tensions in order to allow other researchers to position the inference that will have been produced by the researcher. When several researchers have produced their inferences in relation to models, it is then possible to see the vectors that guide their cognition, and therefore to understand how reality is represented by all of their visions.

Essentially, the way we translate the world speaks to realities that are not illusions as much as real phenomena. The real question is therefore not: what is reality without these biases, but rather: what the sum of all these phenomena allows us to understand about the processes at play in human functioning.

This does not mean on the other hand that all perception testifies to THE truth, and acts as knowledge. What do we mean by that? Isn’t it ultimately a contradiction to claim ONE truth? If all perceptions are ingrained and bear witness to one end of the process involved, don’t they all act as reality?

Let’s put things in perspective. All statements expressed by individuals speak to some part of the reality, but not necessarily to the literal meaning of their words. Words more or less translate our thinking, and therefore there is already at this level a margin of error as to the meaning that the individual would have wanted to express. Then individuals make inferences about the world, and those inferences can be imprecise, or incomplete, as we expressed earlier. The more inferences we make in silo, that is, in a system that does not extend to potentially contradictory sources of information, the more likely it is that these inferences become biased in a particular direction. Amplified, a thought that seeks only to confirm itself will not take its counterexamples into account, and will not be able to rectify its own mistakes, eventually leading to a paradigm that does not allow any valid and usable prediction. So, not every thought is necessarily a thought that correlates highly with reality.

We see the examples with the conspiracy theories which abound in 2020. These theories are carried by people who seek to confirm their position by regrouping, and by gradually isolating themselves from any alternative perception of the facts which they connect between them. By refusing to take counter-examples into account, and denigrating the validity of the types of data exposed to them, it becomes difficult to transform their paradigm into a useful source of prediction.

On the other hand, is there a level of reality that is witnessed by these types of speech? These types of speeches testify to a social need that is shared by a large number of people. Real distress based on failing structures can be read there, when one analyzes these phenomena in their larger context. The nature of the failure can be understood from the discourse produced by these individuals. It is the strength of the social sciences to be able to integrate statements of more or less useful literal value in relation to common objectives, and to transform them into a source of true statements.

If we take all of these concepts into account, we can tackle a problem of similar tenor that arose along with Queer theory.

Thanks to the work and activism of LGBTQIAP2S + groups, new identifications have emerged, bringing with them new phenomenologies. Not necessarily having common languages, the individuals concerned had to work to classify their own experiences on the basis of their subjectivity. Research on this subject therefore also had to adapt to changing realities, which no longer coincided with the previous, largely binary, majority paradigm. Neither having the appropriate language, or the mass of data sufficient to make very clear inferences, the researchers had to rely on more qualitative types of data and limited in their scope of generalization.

From our perspective, and based on what we’ve raised above, this is actually a source of strength. The theorization of this phenomenon started from the start of fragmented conceptualizations, anchored in realities conscious of their positions. The language was built together, and allowed community members to document their processes. We therefore have an abundance of perspectives that seem marginal, but which allow us to trace plural mechanisms that testify to a deeper reality than the previous system. Thus, we can now make more varied predictions, and potentially moreprecise in their granularity than would have been possible before.