Comparing Research Philosophies

Reading this, I felt like many of these assumptions are taught as goals in econometrics class. Like predicting/showing a true relationship or observable effects. We might have considered that some events might not be included in our model, but not that some events might not be observable (or quantifiable) at all, or at least not in an objective way.

Very strong statistical approach that hardly allows for newer methods and has a one-sided effect. Somehow illustrates the problem of the positivism argument.
I would disagree with the statement that the world is always experienced objectively. From a biological point of view alone, the eye cannot grasp all aspects of the world and many impressions are already unconsciously filtered out as irrelevant in the brain. Or does this approach already include the partially objectified view?
Moreover, if the tool of the approach is language, what are promises supposed to symbolize? Something else was meant subjectively than what was said objectively.

Positivist theory relies on objectivity in research but that can be difficult to achieve when researchers are still humans with emotions and biases and ultimately incapable to be completely impartial. It uses a lot of approaches that are similar to those in natural sciences, even though economics itself is a social science. An example of this would be the simplification of reality through models with only one dependent variable in order to prove a causal relationship. That would work if the investigated phenomenon naturally has one dependent variable, but if there are more and some have to be avoided, then the simplified model may not necessarily reflect the real relationship that is studied. In economics, positivist ontology would be inefficient for a more complex issue that requires understanding how social and economic constructs interact and influence each other.

I share many of the sentiments expressed, particularly trouble with the notion that there exists an objective "truth" that can be identified, quantified, and aligned to some natural or general law as per the positivist approach. It seems that this philosophy undergirds what is taught in econometrics and mainstream economics research, where quantifiable data and statistical analysis are heralded for their objectivity and rigorousness, yet little attention is paid to how this type of research and worldview is, too, subject to bias, human influence, and social forces. While there is perhaps merit in positivism's concreteness and systematic approach, it is challenging to reconcile its quest for a singular, objective reality in the face of a heterogeneous and multi-layered world.

While it is important to attempt research that is unbiased and "objective," it is also important to recognize the fact that not all research can be completely objective. Positivism is in pursuit of an objective reality and objective results, however, bias will always play a role in research and especially in economics. The study of economics almost forces scholars to choose theories they believe in or develop their own theories. This causes them to have underlying biases about what they want to prove or not, which is inevitable. This is often seen in econometrics, where numbers and data are seen as objective and possible biases are ignored. It is vital, as a researcher, to understand how problematic it is to assume all data as an objective reality.