5.c) Nature of intelligence: 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) for the intelligence.

The analysis of intelligence through the concepts of Mendel's laws of recessive and dominant genes or, more appropriately, the determination of the criteria to identify the significant chromosome or gene and their mechanisms of expression.

The Moon on the rocks (Public domain image)
The Moon on the rocks

The outcomes of the corresponding correlation and multiple regression graphs show how the sorting criterion based on M1F1 is excellent, confirming the predictions of behavior corresponding to the genetic expression mechanisms derived from the presence of the LoVeInf method regarding the nature of intelligence.

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

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 - Centred variables T1-d, X3 and X6
M q041 11,79 0,67 q042 12,14 0,71
P q043 12,28 0,69 q044 14,38 0,80
2F2M q045 9,20 0,56 q046 12,39 0,70

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 a bit inferior to the M1F1 arrangement criterion.

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 product of the model is substantially more inferior with 2F2M than with the M1F1; therefore, a more rigorously assumption concerning 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. This fact 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 can be made with original variables, although the results are worse than with centered ones.

A curiosity of this model 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.