5.c) Nature of intelligence: Validation of the Method of Logical Verification of Information (LoVeInf)

The main goal of this work was not to verify the hereditary nature of intelligence but to demonstrate the Logical Verification of Information method (LoVeInf) pointed out by the Conditional Evolution of Life (CEL).

In other words, the analysis aims to determine the logical criteria to identify the significant chromosome and their mechanisms of expression within the laws of Mendel.

Analysis of Method LoVeInf (Public domain image)
One of the graphs of the LoVeInf method analysis

The outcomes of the correlations and multiple regression graphs show how the sorting criterion based on *M1F1 is excellent, confirming the genetic expression mechanisms derived from the LoVeInf method regarding the innate character of intelligence.

With the LoVeInf method and the laws of Mendel, the children's variables C would be the *M1F1 component with a 50% probability.

From another point of view, function R is also excellent, both as the goal function and as an arrangement criterion in the simulation model. It makes sense because it incorporates the effect of the genetic combination in agreement with the laws of Mendel. Despite, it is inferior to the *M1F1 arrangement criterion.

SOCIAL MODEL: METHOD LoVeInf Statistical study on IQ
Order Objective function
R M & F
Graphs GMCI r² max. Graphs GMCI r² max.
3 - Original variables T1, T4 and WB
M q031 8,48 0,61 q032 9,16 0,69
F q033 9,44 0,59 q034 12,52 0,78
2F2M q035 7,55 0,61 q036 10,25 0,73
4 - Centered variables T1-d, X3, and X6
M q041 11,79 0,67 q042 12,14 0,71
F q043 12,28 0,69 q044 14,38 0,80
2F2M q045 9,20 0,56 q046 12,39 0,70

In order to be sure of the behavior foreseen by the LoVeInf method, it is possible to check a particular rearrangement criterion: the opposed order of *M1F1, that is to say, the order of the vector formed by the grater values of M2 and F2, that we will call *2F2M.

The result of the model is inferior with *2F2M than with the *M1F1; therefore, a rigorous assumption would be that the LoVeInf method, or something similar, is operative in the inheritance of the characters associated to cognitive functions.

The precision of the results is critical to maintaining a certain degree of confidence in the interpretations; when the lines corresponding to C variables and their different groupings in the graphs follow a clear tendency, it seems that the results are not a consequence of statistical coincidences. It is especially visible within the analysis of variables X3 and X6.

Another observation of the behavior of the centered variables is when using the vectors M of the mothers and F of the fathers as statistical ordering criteria.

For these two vectors of the progenitors, the result of the simulation is superior compared to variable *2F2M, but it continues being quite inferior in respect to *M1F1.

The same comparisons with original variables produce results less powerful than with centered ones.

A curiosity of this analysis is the different behavior between *M and *F because up until now, there were no hints for it. In the corresponding graphs (following the links), vector *M seems slightly more significant as rearrangement criterion whereas its correlation with X3 and X6 was smaller than vector *F. Regardless of the correlation level of *M and *F separately; it seems as if their lines or curves were mirror images of one another.

Sociologically speaking, this subject of the nature of intelligence and mirrors has always been susceptible between M and F. Surely, when the first humans realized that women always had the children, there were tremendous and violent discussions about the importance of matriarchy, especially, in its economic aspect.