First, I doubt you have searched for this article, but if you have, welcome and I recommend you check out The Navigation Codex before reading this. If you haven’t searched for my article on why I use meta-analysis studies when discussing The Navigation Codex, then you clicked from an article and have the same scientific and inquisitive mind as I do – so kudos.
This article will be concise and precise. Let’s jump in.
What is a Meta-Analysis
A meta-analysis is a study that collates data from many individual studies to get an overview of what that data shows.
It allows a more focused conclusion using broader datasets. In short, more information to evaluate allows more keen understanding of what that data is saying.
Why I Focus on Meta-Analysis for The Navigation Codex
I focus on meta-analysis when discussing The Navigation Codex because it is the fairest way I can evaluate what existing materialist data says.
It allows me to reduce the following:
- Researcher bias
- Financial bias
- Limited or incomplete datasets
- Narrow sample sizes
All of which I will briefly explain below.
Reducing Potential for Researcher Bias
Researcher bias is absolutely rife in materialist academic circles.
This isn’t necessarily corruption on a personal level. In most cases, researchers apply for funding, and they only receive funding if the work they are doing builds on the established narrative and the findings support it.
It is very rare for researchers to break away from the mainstream narrative, and when they do, they are cut off financially, discredited and ostracised. A great example in pop culture is Sabine Hossenfelder, who is a high profile casualty of the system, but believe me she is one of thousands of researchers each year who have their reputations destroyed for failing to toe the line.
With this in mind, it is no surprise that the overwhelming majority of scientists stick to the consensus.
Peer review reinforces this. If you have a theory that breaks the narrative, you almost certainly won’t be entertained for peer review. Peer review is one big circle jerk.
By using meta-analysis, although researcher bias will inevitably remain, the dataset is so large that it becomes difficult for researchers to skew the conclusions in the way they want to.
Reducing Potential for Financial Incentive Bias
Why does consensus exist? Well, it is institutional corruption and corporate financing. Big pharma for example funds the majority of healthcare research globally.
Do you think that research is ever going to champion natural remedies over patentable pharmaceutical products?
Therein lies the problem. Researchers rely on the funding, the funders want specific outcomes, and the whole process becomes circular self-validation rather than scientific progression.
Meta-analysis while sometimes will be funded by financial players, more often than not they are compiled by independent research groups who are trying to better understand the data from individual studies.
Either way to some degree, using a meta-analysis reduces the impact of the perverse financial incentives that permeate modern academia.
Reducing Scope for Erroneous Data
Individual studies are only as good as the data they can collect and include.
Most individual studies have small sample sizes that are wholly inappropriate to draw meaningful conclusions from and some even remove datapoints that contravene the narrative the researchers are propping up.
It is also no secret that scientists have in some cases completely manipulated the dataset they use to get a specific outcome.
Meta-analysis pulls datasets from multiple individual studies and while it might not be perfect, it is far better than relying on the integrity of individual studies.
Increasing Sample Size
Ultimately, a scientific study should be able to point us to an answer. What does the data tell us about the population at large? Can we understand this information in a way that helps everyone?
Individual studies simply don’t get the funding or have the scope to conduct large sample size studies. It is very common for individual studies to focus on a sample size under 100 people. Which is useless – not just poor, it is actually useless for understanding what the findings mean in relation to the general population.
Meta-analysis will pull datasets from multiple individual studies. Sometimes upwards of a 100 individual studies. This immediately allows researchers to make meaningful conclusions as the total sample size makes it more representative of the population at large.
Understanding the Limitations Even Meta-Analysis Has
A meta-analysis is still flawed in that it relies on the datasets of individual studies that are sometimes questionable. With this in mind, even when assessing meta-analysis, it is important to realise some of its foundational data will be bad.
This means a meta-analysis is not perfect. It is however more complete than the individual studies that form it.
It would also be remiss to suggest researcher bias and financial incentives don’t exist in meta-analysis. They absolutely do. However as mentioned earlier the scope of data makes it much harder for researchers to justify biased findings.
The Navigation Codex in a Formative Stage
The Navigation Codex is in a formative stage, not yet unleashed on the world and not yet able to command scientific rigour from academic communities.
My hope is that as time goes on and the Codex makes its way naturally out into the world there will be engagement from the academic community and then I am happy to be robust in presenting the theory.
Until that point, I am confined to funding my own research and relying on existing materialist studies. Not ideal but it is what it is.
Hopefully this explains why I prefer meta-analysis over individual studies wherever practicable and helps you understand that scientific rigour is important for The Navigation Codex – it is not some new age hokum, there is a foundation here that will be elaborated on in due time.
As always, feel free to reject anything I say, it is absolutely your choice about how you navigate and what you believe!
