Entics, the science of entities, otherwise known as the entic
science, is a discipline that has a long history, but is rarely named
as such. It is viciously divided between an empirical approach
(biology, physics, etc.) and metaphysical philosophy (ontology,
how things exist).

Entics may be described initially in terms of an item, and the
datum in which the item is understood.

Depending on the manner in which entities are interpreted, the
datum may take the form of mathematical dimensions, a context
of interaction (such as intelligent networks), or a logical
relationship such as a philosophical system or linguistic pattern.

Ideally, entities (items) have some kind of significance in terms of
the formal context in which the item is being interpreted. A
common result is to find that the item falls into the following

1: Trivial (not affecting the context at all).
2: Un-exceptional (not affecting the context meaningfully).
3: Typical (affecting the context in a normal way).

Additionally, some items may in some cases be (0:) completely
meaningless (be careful with this by using absolute criteria), but
otherwise if they don't fit into the above, they fall into the
following more advanced categories:

4. Functional (following a predictable pattern).
5. Organized (having a particular effect).
6. Exceptional (following a characteristic pattern).
7. Unique (having a highly notable effect or pattern).
8. Game-changing (changing the way the
datum behaves)

As can be seen, this initial type of analysis results in ranking
items in terms of their uniqueness, with the assumption that
unique internal logic defines unique external logic.

Next, at a more advanced level we have relations of multiple
objects (symbols) or items (entities), and we wish to find common
significance amongst them.

This can be done through the following properties:

1. Existence (Yes / No).
2. Commonality (Degree / Characterization)
3. Oppositeness (Opposition / Exclusion)
4. Modal Similarities (Opposed but similar?
    Basically similar or basically different?)
5. Unique Attributes (Common and different classifications)

Readers may note the similarity to principles from syllogisms,
such as existence and exclusion.

This process serves to classify in exactly which ways, vis. the
earlier categories, these items, objects or entities express
exterior attributes.

An important tool in entics is the concept of 'digging' which is an
additional extension of analysis which asks us to get the most out
of any one concept. Effectively, the only limitation on digging is
normativity which defines that a previous object is already

Thus, a first rule of entics is that
items tend to be significant. This
is because the only possibility of finding significance for an object
is finding some way in which it has significant for other objects
which are already significant. Thus, an object has to be
doubly-significant to have special significance. Simply relating
with one significant object is not enough, and relating with two
objects may require some form of logic.

A second rule is that
items express interior logic through
relevance, or else through experience

Thus, some of the broadest possible categories of relevance and
experience might be helpful:


1. Appearance.
2. Influence.
3. Symbolism.
4. Scintillation.

1. Notion.
2. Representation.
3. Excitation.
4. Awareness.

Thus we get the primary logic for internal entities through the

{(Appearance & Influence & Symbolism & Scintillation)
(Notion & Representation & Excitation & Awareness)}

Thus, relevance and experience are fundamentally based on
causes (scintillations, etc.) and origins (notions, etc.).

Thus, an entity may be explained generally as a
causal origin.

V. (The role of Quantificcation).

In some cases a system exists exclusively through quantification,
and it is quantification that expresses the existence of system.
This is true for example, with simplified concepts of evolution or
Moore's Law of Computing (that technology quadruples its
complexity every six months, or something like that).

In these cases, the entity (such as technology) represented by the
system (such as technological growth) amounts to a power
difference. Thus, the system amounts to a number such as 2,  3 or
4 which represents an exponent on a field of data.

Most other differences expressed in these terms are variations
within pre-existing data, such as can be accommodated  by adding
or subtracting large numbers from the equation's data set. For
example, with anthropological data about someone's age, we
might predict longer potential age the longer someone succeeds
to survive. So, actual age can be approximated as an extended
tail with a probability of
(1 / sq root of n) + (1 / the average life
expectancy in years)
, where n is the number of years lived.