"Theory of integrative levels claims that the natural world is organized in a series of levels of increasing complexity: from physical particles and molecules, through biological structures, to the most sophisticated products of human thought. Each level cannot exist without the lower ones (EG there are no organisms not being formed with atoms), but at the same time it has additional emergent properties not found at the lower levels (EG organisms can be said to be alive or dead, while atoms cannot). This view goes beyond the traditional opposition between reductionism and vitalism, both of which have important limitations.

The ideas of integrative levels and emergence can be found in some form in Western philosophy since at least 19th century [Blitz 1992, Grolier 1974], and generally agree with the naturalistic point of view adopted by many modern scientists. However, it was only later that they were formulated in a more explicit way, by philosophers James K Feibleman [1954] and Nicolai Hartmann [1940, 1942]. Hartmann's work is especially relevant for the foundations of ontology, the branch of philosophy dealing with the structure of reality." - Wikipedia

• Errors Based on Misunderstanding of Emergence

  • reductionism -- everything is just physics (neglects the emergence at each level)
  • vitalism -- a "special spark" is needed for emergence (actually it is the complex, non-intuitive interactions of the parts)

• Level Definition and Ordering

  Levels can be defined and ordered based on rigorous criteria, e.g., aggregates lower level units but not vice-versa. The ordering probably also indicates evolution: e.g., molecule appeared before cells, cells before multi-celled organisms.

  Orderings have been developed on other criteria (see Heylighten) .

• Structure of Levels

  Levels are ordered but form a branching structure rather than a single progression, and many type variations may exist per level.  For example, both living and non-living systems aggregate molecules (organic and inorganic branches). There are many variations of cells within each species and across species. Types in-between standard levels may also exist ("mezoforms").

  Such complex structure is difficult to describe, communicate, and investigate, without use of a model (i.e., complexity management)

• The Big Picture

  Levels constitute a fundamental structure (architecture) of the universe. They thus provide "the big picture" important to understanding how all(?) else fits together. From a view of "systems within systems" this would provide one of the broadest, the most encompassing view.

  A structure based on well-defined levels can provide a clear organizing framework as a basis for managing knowledge of the universe. Reaching agreement about this structure seems to be a priority.

• Objective or Subjective?

  How intrinsic are our levels? Some, especially at the lower end (atoms, molecules, cells), seem based on clear, objective criteria, yet anything conceived by a human is likely to be subjective to some degree. Yet there is broad agreement that the systems at many levels do accurately represent reality.

  Must clearly distinguish between systems/levels meant to represent reality and those meant only as a way to organize our thinking.

• Layered Architecture

  The conventional levels are very similar to a layered architecture developed for man-made systems. This probably indicates something intrinsic about the nature of reality.  Systems that endure are likely to consist of components of components rather than of elements without any intervening component structure. New levels will evolve from exisiting components having stability and efficiency, not from primitive elements. (See Simon's parable of the two watchmakers, i.e., the virtue of components.)

• Key Systems

  Some systems are especially important because they represent a significant new structure and open new lines of evolution. Among these are matter, life, mind and culture (see Henriques' Tree of Knowledge).

• Emergent Property View of Reality

  Reality as we experience it could be viewed as a hierarchy of emergent properties based on the hierarchy of system types. Each system type is an aggregate of the emergent properties of all of its embedded system types. For example, a cell aggregates the emergent properties of molecules, atoms, sub-atomic particles, and quarks, in addition to the properties that emerge at the cell level. Furthermore, the properties of an instance of a system will depend on the varieties of the systems at each level; e.g., whether specific atoms are of hydrogen, clorine, or uranium, whether molecules are water or hydrogen cyanide (meaning an immense number of possibilities). 

  Sorting this out would seem to be a valuable exercise, as it would, for one thing, clearly separate concerns. Conflating the levels providing properties is a major source of confusion. Quality management emphasizes addressing the right level ("most problems are in the system", "you can't optimize the whole by optimizing the parts individually", "dissolving problems").

  A system at one level may have "roles" at a higher level, and the two levels are often confused. Clarifying such relationships would be helpful. For example, hemoglobin is a molecule with certain "chemical" properties at the molecular level. At a higher level, hemoglobin plays a role of oxygen transporter within the context of the circulatory system of living systems. A role describes how some part of the function of a lower level system is integrated into a higher level system. While hemogolobin can exist as an individual molecule, if it didn't play a useful role as part of another system, little would be extant.

  This promotes a view of the universe that is more process- than thing-oriented. The emergent properties at every level depend on the interactions of the parts at the next lower level, which in turn depend on the interactions of their parts, etc. This could be viewed as "interactions all the way down", with the function of "thing-ness" as no more than a convenient way to refer to groups of interactions. 

  Representing this complexity in a way that is understandable requires a model.