Q&A: Meaning Symbol Sign and Mind (Part 2)

On one of my recent posts, a commentor named “psycho” asked me some very good questions. I decided I needed to respond in more detail than just a single comment reply. I respond in pieces below, so just for context, here is psycho’s entire original comment.

But if you take more meanings, and put them together to get yet another meaning. Don’t you feel like those meanings were again like symbols creating a new meaning?

In my understanding, every bit of information is a symbol – what is represented by the invididual neurons in the brain. And if you take all related bits (that is neurons, symbols), and look at it as a whole, what you get is meaning.

The sentence is a symbol, and it is made of word-symbols. And the list of word-symbols makes a meaning. Which, when given a name (or feeling), becomes a symbol, that can be further involved in other meanings.

I’ll respond to each paragraph in separate posts, in order to get all of my thoughts down in a reasonably readable fashion. Part one covered the first paragraph. Here is part two where I cover the rest of my thoughts.

Symbols in the Mind

In my understanding, every bit of information is a symbol – what is represented by the invididual neurons in the brain. And if you take all related bits (that is neurons, symbols), and look at it as a whole, what you get is meaning.

I’m not a neurologist or any kind of brain scientist by any means, so I could eventually be proven wrong on this, but what a neuron represents, to me is not a symbol and not a sign and not a specific meaning. I know I read somewhere of a brain experiment (using MRIs I think) where the image of Jennifer Aniston presented visually during a brain scan caused only a single neuron to fire. I recall that the interpretation given was that the entire concept of “Jennifer Aniston” was stored in one singular neuron.

I guess I just don’t buy it. What if the meaning of that neuron was more along the lines of “a famous person whose name I forget” or “I recognize a face I’ve seen on ‘Entertainment Tonight'”? The fact of it is, the experimenters drew a conclusion on a correlation that not even their subject would be able to explain or confirm.

Then there is some hypothesis that memories and meanings are distributed across the brain in such a pattern as to suggest more of a holographic storage mechanism (where damage in one area of the brain is overcome by stimulation and growth and retraining).

I think that memory and meaning is essentially an EXPERIENCED thing. That the physical stimuli produce a complex of sensations through re-activation of neurons that causes the brain itself to “sense” the memory. I don’t think this qualifies as a symbollic sensation, being a much more holistic, “analog” experience not unlike the original. If every bit of information were a symbol, then I think we’d be just as hard-wired as computers to recognize only one set of sensations and meanings. Our experience being more fluid, it allows us to be much more creative in the aspects and portions of sensation that we recognize and name. As an individual I have full freedom to separate the signal from the noise, the foreground from the background, as I fancy. I can “slice and dice” me experience of sensation in anyway that I find meaningful, and if I communicate it to you, then you can see what I see just like that. In other words, working with the “analog” of my sensations is a much more powerful, creative endeavor than merely encoding and decoding “digital” symbols.

That’s my two cents on that thought.

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Q&A: Meaning Symbol Sign and Mind (Part 1)

On one of my recent posts, a commentor named “psycho” asked me some very good questions. I decided I needed to respond in more detail than just a single comment reply. I respond in pieces below, so just for context, here is psycho’s entire original comment.

But if you take more meanings, and put them together to get yet another meaning. Don’t you feel like those meanings were again like symbols creating a new meaning?

In my understanding, every bit of information is a symbol – what is represented by the invididual neurons in the brain. And if you take all related bits (that is neurons, symbols), and look at it as a whole, what you get is meaning.

The sentence is a symbol, and it is made of word-symbols. And the list of word-symbols makes a meaning. Which, when given a name (or feeling), becomes a symbol, that can be further involved in other meanings.

I’ll respond to each paragraph in a separate post, in order to get all of my thoughts down in a reasonably readable fashion. Here is part one.

Construction of Symbols

But if you take more meanings, and put them together to get yet another meaning. Don’t you feel like those meanings were again like symbols creating a new meaning?

I try to make a very strong statement of the difference between symbols, signs and their “meanings”. Perhaps I’m being too analytical, but it allows my to think about certain types of information events in a way I find useful in my profession as a data modeller. So let me try to summarize here the distinctions I make, then I’ll try to answer this question.

First, in my writings, I separate the thing represented by a symbol from the thing used as the representation. The thing represented I call the “concept” or “meaning”. The thing which is used to represent the concept I have termed “the sign”.  A symbol is the combination of the two. In fact, a specific symbol is a discrete object (or other physical manifestation) built for the express purpose of representing something else. That specific symbol has a specific meaning to someone who acts as the interpreter of that symbol.

As I have come to learn as I continue reading in this subject area, this is a somewhat ideosyncratic terminology compared to the formal terms that have grown out of semiology and linguistics. To that I say, “so be it!” as I would have  a lot of re-writing to do to make my notions conform. I think my notions are comparable, in any case, and don’t feel I need to be bogged down by the earlier vocabulary, if I can make myself clear. You can get a feel for some of my basic premises by poking around some of my permanent pages, such as the one on Syntactic Media and the Structure of Meaning.

There is obviously a lot of nuance to describing a specific symbol, and divining its specific meaning can be a difficult thing, as my recurring theme concerning “context” should indicate. However, within my descriptive scheme, whatever the meaning is, it is not a symbol. Can a symbol have several meanings? Certainly. But within a specific context at a specific time, a specific symbol will tend to have a single specific meaning, and the meaning is not so fluid.

How do you express a more complex or different idea, then? It is through the combination of SIGNS which each may represent individual POTENTIAL concepts that I am able to express my thoughts to you. By agreement (and education) we are both aware of the potential meanings that a specific word might carry. Take for example this word (sign):

blue

When I show you that word in this context, what I want you to recognize is that by itself, I am merely describing its “sign”-ness. Those four letters in that combination form a word. That word when placed into context with other words may represent several different and distinct ideas. But by itself, it is all just potential. When you read that word above, you cannot tell if I’m going to mean one of the colors we both might be able to see, or if I might be about to tell you about an emotional state, or if I might describe the nature of the content of a comedian’s act I just saw…

While I can use that sign when I describe to you any of those specific meanings, in and of itself, absent of other symbols or context, it is just a sign with all of those ambiguous, potential meanings, but in the context of our discussion, it has no specific meaning.

It has a form, obviously, and it has been constructed following rules which

Photo of an Actual Stop Sign In Its Normal Context

you and I now tacitly understand. Just as a stop sign has been constructed following rules we have been trained to recognize.

Imagine now a warehouse at the Department of Transportation where a pile of new stop signs has been delivered. Imagine they are laid flat and stacked on a pallet, just waiting to be installed on a corner near you.

While they lay in that stack, they certainly have substance, and they each have the potential to mean something, but until they are placed into a proper context (at a corner by a road) their meaning is just as ambiguous as the word sign above. If you were driving a fork lift through the warehouse and came upon the pallet, would you interpret the sign right then as applying to you? Probably not! Could you say, just be looking at an individual instance of a sign, exactly which cars on which road it is intended to stop? No, of course not.

So this is the distinction between the sign and the meaning of a symbol. The sign is a physical construct. When placed into a recognized context, it represents a specific meaning. In that context, the sign will only carry that one specific meaning. If I make another instance of the sign and put it in a different context, while the signs may look the same, they will not mean the same, and hence I will have made two different symbols.

Just to be perfectly clear on the metaphor I’m presenting, here is a “pile” of signs (words) which I could use in a context to express meaning:

blue

blue blue

blue blue blue blue

Now let me use some of them and you will see that given a context (which in this case consists of other word signs and some typcal interpretations) I express different meanings (the thoughts in your head when you read them together):

once in a blue moon

blue mood

blue sky project

blue eyes crying in the rain

But make no mistake, while i have now expressed several different ideas to you using the same sign in different contexts, they are each, technically, NOT THE SAME SIGN AT ALL! Rather they are four examples of a type of sign, just as each of the stop signs on that pallet at the DoT are examples of a type of sign, but each is uniquely, physically its own sign! This subtlety is I think where a lot of people’s thinking goes awry, leading to conflation and confusion of the set of all instances of a sign with all of the concepts which the SET of signs represents.

To make this easier to see, consider the instance of the word (sign) “blue” above which I have colored red. That is a specific example of the “blue” sign, and it has a specific, concrete meaning which is entirely different from the word (sign) “blue” above which I have colored green.  The fact that both phrases have included a word (sign) of “blue” is almost coincidental, and does not actually change or alter the individual meanings of the two phrases on their own.

Finally, since I have belabored my nit-picking a bit, if I were to re-word your initial statement slightly to use the terminology I prefer on this site, It would change to:

But if you take more [signs], and put them together to get yet another meaning. Don’t you feel like those [signs] were again like symbols creating a new meaning?

And to this question, it should be clear, that my answer is “Yes, precisely: when you put other signs together, you create new meaning”.

soda vs pop vs coke (via chai T)

Someone has been doing some good research. This doesn’t change my earlier post, but kind of corroborates what i was trying to say.

soda vs pop vs coke it amazes me the things people will bicker over. where i grew up, everyone called it soda, so that is what i call it. when my first girlfriend and i started becoming friends and then dating, we had this conversation a lot. she was from southern minnesota and adamant about correcting me anytime i asked for a soda. it got to the point where i would just request a beverage by it's name. one day, when she took me home (to her very catholic, homophobi … Read More

via chai T

What is “Comparability”?

What is “comparability“? Basically it is a relationship between two things. If two things are “comparable“, in general parlance, then they are similar in some aspects. They share common features or functions. They are not “equal” necessarily, as there may be important differences between them. In fact, it may be that the interesting aspect of the comparison made between the two objects is in their difference, more than in their similarity. However, a test for equivalence is a very common comparison to make for things that are comparable.

Typically, the comparison will be made with respect to some common constraint, from a particular point of view, or within a particular context. Any two things can be compared, although the meaningfulness an dutility of the comparison is not always guaranteed. The most meaningful/useful comparisons will occur within a context where the two things are strongly similar.

For a simple example, consider comparing ants and humans. In order to do this meaningfully, a context for comparison must be established, and a set of common properties must be recognized. Comparing the “wing span” property of ants an dhumans would be a meaningless comparison, since humans have no wings, and most ants do not either. Comparing the anatomy of an example of each type of creature might form a context where the property “number of limbs” could generate a meaningful result.

Comparing the “strength” property of a human versus an ant may also be meainingless or at least misleading. The absolute strength of the human will be much higher than the absolute strength of the ant. However, comparing the “strength relative to weight” of each creature can tell us something much more interesting. The relative strength, where the weight of objects each creature can pick up is divided by the body mass (weight) of the creature.

Hence, while comparing absolute strength between ants and humans is meaningful, it is not terribly useful. Once the relative strength has been calculated, a meaningful and potentially useful comparison can be made, giving us an “apples to apples” comparison. By adjusting the strength property of each creature, we have created a comparison which is both meaningful and useful.

In this example, it is useful from the standpoint that the comparison is more understandable.

We have effected this improvement in the meaningfulness by establishing the context of comparison through the application of functions to the values of the creatures native properties. In other words, we have applied similar “conversion” functions in similar ways to the ant and human “strength” and “weight” properties to derive two new properties which are <em>more</em> comparable than each of the original values on their own.

The approach we took was to find where two things are analogous – where their similarties lie – and then to translate their analogous properties into meaningful and useful new values which can be compared.

The idea expressed by the term “comparability” implies that there will be similarities between the things compared. It also presupposes the expectation if not the a priori knowledge that there will be some differences, and that the differences between analogous properties can provide insight and knowledge.

Comparability: How Software Works

Back in 1990, I was working on a contract with NASA building a prototype database integration application. This was the dawn of the Microsoft Windows era, as Windows 3.0 had just been released (or was about to be). Oracle was still basically a start-up relational database vendor trying to reach critical mindshare. The following things did not yet exist which we take for granted today (and even think of as kind of out dated):

  • ODBC – allowing standardized access to databases from the desktop
  • Microsoft Access and similar personal data management utilities
  • Java (in fact most of the current web software stack was still just the twinkles in the eyes of their subsequent inventors)
  • Message-based engines, although EDI techniques existed
  • SOA and XML data formats
  • Screen-scrapers, user simulators, ETL utilities…

The point is, it was still largely a research project just to connect different databases that an enterprise might be using. Not only did the data representational difficulties that we face today exist back in 1990, but there was also a complete lack of infrastructure to support remote connection to databases: from network communication protocols, to query interfaces, to security and session continuity functions, even to standardized query languages (SQL was not the dominant language for accessing data back then), and more.

In this environment, NASA had asked us to prototype a generic capability that would permit them to take user search criteria, and to query three different database applications. Then, using the returned results from the three databases, our tool was to generate a single, unified query result.

While generally a successful prototype, during a critical review, it became clear to NASA and to us that maintaining such an application would be horribly expensive, so the research effort was ended, and the final report I wrote was delivered, then put into the NASA archives. It is just as well too, because within five years, much of the functional capabilities we’d prototyped had started to become available in more robust, standards-based commercial products.

What follows is a handful of excerpts from the final report, which while now out of context, still expresses some important ideas about how software symbols actually work. The gist of the excerpt describes how software establishes the comparability and sometimes the equivalence of meaning of the symbols it manipulates.

In a nutshell, software works with memory addresses with particular patterns of voltage (or magnetic field direction) representing various concepts from the human world. Software is constantly having to compare such “structures” together in order to establish either equivalence of meaning, or to alter meaning through the alteration of the pattern through heavily constrained manipulations. The key operation for the computer, therefore, is to establish whether or not two symbols are “comparable“. If they are not comparability, quite literally, then the computer cannot reliably compare them and produce a meaningful result.

Without further ado, here are the important excerpts from the research study’s final report, which I wrote and delivered to NASA in November 1990.

“Database Integration Graphical Interface Tools, Future Directions and Development Plan”, Geoff Howe, November 1990

2.2 The Comparability of Fields

There are many kinds of comparisons that can be made among fields. In databases, the simplest level of comparability is at the data type level. If two fields have the same simple data type (e.g., integer, character, fixed string, real number), then they can be compared to each other by a computer. This level of comparability is called “basal comparability”. Thus, if fields A and B are both integers, they can be combined, compared and related in any way appropriate for two integers.

However, two elements meeting the qualification for basal comparability may still be incomparable at the next level, that of the syntactic level. The syntactic level of comparability is that level in which the internal structure of a field becomes important. Examples of internal formats which might matter and might be important at this level include date formats, identification code formats, and string formats. In order to compare two fields in different formats, one or the other of these fields would have to be converted into the other format, or else both would have to be converted into a third format. The only meaningful comparisons that can be made among the fields of a database or databases must be made at the syntactic level.

As an example, suppose A is a field representing a date in Julian format, and suppose B is a field representing a date in Gregorian format. Assuming that both fields are stored as integers, comparing these dates would be meaningless because they lack the same syntactic structure. In order to compare these dates one or the other of these dates would have to be converted into the other format, or else both would have to be converted into a third format.

Unfortunately, having the same syntactic structure is not a guarantee that two fields can be compared meaningfully by a computer process. Rather, syntactic comparability is the minimum requirement for meaningful comparison by computer process. Another form of comparability must be incorporated as well, that of semantic comparability. Semantic comparability is based on the equivalence of the meanings attached to the contents of some pair of data items. The semantics of data items are not readily available to computer processes directly; a separate description in some form must be used to allow the computer to understand the semantic equivalence of concepts. Once such representation is in place, the computer should be able to reason over the semantic equivalence of concepts.

As an example of semantic comparability consider the PCASS fields, ITEM PART NUMBER from the FMEA PARTS table of the PCASFME subsystem, and CRIT_LRU_PART_# from the CRITICAI LRU table of the PCASCLRU subsystem. Under certain circumstances, both of these fields will hold the part numbers of “line replaceable units” or LRUs. Hence, these fields are semantically comparable. Given a list of the contents of ITEM PART NUMBER, and a similar list for CRIT LRU PART #, the assumption can be made that some of the same “line replaceable units” will be referenced in both lists.

Semantic comparability is useful when integrating data from different databases because it can be used to indicate the equivalence of concepts. Yet, semantic comparability does not imply syntactic comparability, and thus both must be present in order to satisfactorily integrate the values of fields from different databases. A definition of the equivalence of fields across databases can now be offered. Two fields are equivalent if they share the same base type; if their internal syntactic structure is the same; if their representational domains are the same; and if they represent the same concept in all contexts.

2.3 Heterogeneous Data Dictionary Architecture

 The approach which seems to have the most documentary support in the research for solving the integration of heterogeneous distributed databases uses a two-tiered data dictionary to support the construction of location-independent queries. The single data dictionary, used by both the single-site database management system, and the homogenous distributed environment, is split in two across the physical-conceptual boundary. This results in a two-level dictionary where one level describes in detail the physical fields of each integrated database, and the second level describes the general concepts stored across systems. For each unique concept represented by the physical level., there would be an entry in the conceptual level data dictionary describing that concept. Figure 2 shows the basic architecture of the two level data dictionary.

As an example of the difference between the conceptual and physical data dictionary levels, consider again the field PCASFME.FMEA PARTS.ITEM PART NUMBER. This is the full name of the actual field in the PCASS database. The physical level of the data dictionary would have this full name, plus the details of how this field is represented (character string, twelve places long). The conceptual level of the data dictionary would contain a description of the contents of the field, and a conceptual field name, “line replaceable unit part number”. Other fields in other tables of PCASS or in other databases may also have the same meaning. This fact poses the problem of mapping the concept to the physical field, which will be described below. Notice, however, how much easier it would be for a user to be able to recall the concept “line replaceable unit part number”, as opposed to the formal field name. This ease of recall is one of the major benefits of the two-level data dictionary being proposed. Two important relationships exist between the conceptual and physical data dictionaries. One of the relationships between fields of the conceptual level data dictionary and fields of the physical level data dictionary can be characterized as one-to-many. That is, one concept in the conceptual data dictionary could have many physical implementations. Identification of this type of relationship would be a matter of identifying and recording the semantic equivalences across system boundaries among fields at the physical level. All physical fields sharing the same meaning are examples of this one-to-many relationship.

Within the PCASS system, the concept of a line replaceable unit part number” occurs in a number of places. It has already been mentioned that both the ITEM PART NUMBER field of the FMEA_PARTS table, and the CRIT LRU PART # field of the CRITICAI_LRU table, represent this concept. The relationship between the concept and these two fields is, therefore, one-to-many.

The second type of relationship which may also be present, depending on the nature of the existing databases, relates several different concepts to a single field. This relationship is characterized as “many-to-one”. Systems which have followed strict database design rules should result in a situation where every field of the database represents one and only one concept. In practical implementations, however, it is often the case that this rule has not been thoroughly implemented, for a variety of reasons. Thus it is more than likely, especially in large database systems, that some field or set of fields may have more than one meaning under various circumstances. Often, these differences in meaning will be indicated by the values of other associated fields.

As an example of this type of relationship, consider the case of the ITEM PART NUMBER field of the PCASS table FMEA PARTS in the FMEA dataset one-more time. This field can have many meanings depending on the value of the PART TYPE field in the same table. If PART TYPE is set to “LRU”, the ITEM PART NUMBER field contains a line replaceable unit part number. If PART TYFE is set to “SRU”, the ITEM PART NUMBER field actually contains a shop replaceable unit part number. Storing both kinds of part numbers in the same structure is convenient. However, in order to use the ITEM PART NUMBER field properly, the user must know how to read and set the PART TYPE field to disambiguate the meaning of any particular instance of the record. Thus, the PART TYPE field in the physical database must hold either an “SRU” or “LRU” flag to indicate the particular meaning desired at any one time.

In the heterogeneous environment, it may be possible to find a different database in which the same two concepts which have been stored in one filed in one database, are stored in separate fields. It may in fact be possible that in one or more databases, only one of the two concepts has been stored. This is certainly the case among the separate data sets which make up the PCASS system. For example, in the PCASCLRU data set, only the “line replaceable unit part number” concept is stored (in the field, CRIT_LRU_PART_#). For this reason, the conceptual level of the data dictionary must include both concepts. Then there must be some appropriate construct within the data definition language of the data dictionary system which could express the constraints under which any particular field had any particular meaning. In order to be useful in raising the level of data location transparency, these conditional semantics must be entered into the data dictionary using this construct.

It is obvious now that the relationship between entries in the conceptual data dictionary and the physical data dictionary is truly many to many (see Figure 3). To implement such a relationship, using relational techniques, a third major structure (in addition to the set of tables supporting the conceptual data dictionary and the set of tables supporting the physical data dictionary) must be developed to mediate this relationship. This structure is described in the next section.

2.3.1 Conceptual – Physical Data Mapping

As an approach to implement this mapping from conceptual to physical structures, a table must be developed which relates every concept with the fields which represent it, and every field with the concepts it represents. This table will consist of tautological statements of the semantic equivalence of physical fields to concepts. A tautology is a logical statement that is true in all contexts and at all times. In thiis approach, the tautologies take the following form (please note that the “==” operator means “is semantically equivalent to”, not “is equal to”):

 normalized field f == field a from location A

 The normalized field f of the above example corresponds directly to an entry in the conceptual data dictionary. We call the field, f, normalized to indicate that it is a standard form. As will be described later, the comparison of values from different databases will be supported by normalizing these values into the representation described in the conceptual data dictionary for the normalized field.

Conditional semantics must now be added to the structure to support discussion. Given a general representation for a tautology, conditional semantics may be represented by adding logical operations to the right side of the equivalence. Assume that a new database, D, has a field, d1, which is equivalent to the normalized field, f, but only when certain other fields have specific values. Logically, we could represent this in the following manner:

normalized field f == field d1 from location D iff
field d2 from location D = VALUE1 AND
field d3 from location D = VALUE2 AND …
field dn from location D opn VALUEn

 In more general terms, the logical statement of the tautology would be as follows:

 R == P iff  E

where R is the normalized field representation, P is the physical field, and E is the set of equivalence constraints which apply to the relation. In our part number example, the following tautologies would be stored in the mapping:

Line Replaceable Unit Part Number == PCASFME.FMEA.PARTS.ITEM_PART_NUMBER iff PCASFME.FMEA.PARTS.PART_TYPE = “LRU”

Shop Replaceable Unit Part Number == PCASFME.FMEA.PARTS.ITEM_PART_NUMBER iff PCASFME.FMEA.PARTS.PART_TYPE = “SRU”

Line Replaceable Unit Part Number == PCASCLRU.CRITICAL_LRU_CRIT_LRU_PART_#

The condition statements are similar to condition statements in the SQL query language. In fact, this similarity is no accident, since these conditions wilt be added to any physical query in which ITEM PART NUMBER is included.

From a user’s point of view, implementing this feature allows the user to create a query over the concept of a line replaceable unit part number without having to know the conditions under which any particular field represents that concept. In addition, by representing the general – concept of a line replaceable unit part number, something the user would be very familiar with, this conceptual mapping technique has also hidden the details of the naming conventions used in each of the physical databases.

2.4.2 Integrating Data Translation Functions Into the Data Dictionary

In the simplest case, the integration of data translation functions into the data dictionary would be a matter of attaching to the data mapping tautologies described above a field which would store an indication of the type of translation which must occur to transform a result from its Location-specific form into the normalized form. This approach can be simplified further by allowing translations at the basal level to be identified by the source and target data types involved, and not recording any further information about the translation. It may not be unreasonable to assume that in certain well-defined domains, most of the translation functions required would be either identity functions or simple basal translation functions.

It is now possible to define completely the data structure required to store any arbitrary physical-conceptual field mapping tautology. The data structure would consist of the following parts:

  • concept field – a single, unique concept which the physical projection represents
  • normalized – a reference to the conceptual data dictionary entry used to represent the concept
  • physical projection – the field or set of fields from the physical data dictionary which under the conditions specified in the equivalence constraints represent the concept
  • equivalence constraints – the conditions under which the physical projection can be said to represent the concept
  • translation function – the function which must be performed on the physical projection in order to transform it into the normalized format of the normalized field

The logical statement of the tautology would be as follows:

R = Ft (P) iff E

where R is the normalized field representation, Ft is the translation function over the physical projection, P, and E is the set of equivalence constraints which apply to the relation. The exact implementation of this data structure would depend on the environment in which the system were to be developed, and would have to be specified in a physical design document. Note that instead of the “==” sign, which was defined above as “is semantically equivalent to”, has been replaced by “=” which means “is equivalent to”, and is a stronger statement. The “=” implies that not only is the left side semantically equivalent to the right, but it is also syntactically equivalent.

The Nature and Experience of Semiosphere Boundaries

I have been having an interesting discussion with Sentence First blogger Stan Carey regarding semiosphere boundaries, and I posted the following comment on his site. I thought I’d repeat it here then elaborate on it.

I’m no expert on Lotman (author of many semiotics papers and coiner of the term “semiosphere”), having only begun to read his work, and I also recognize and agree that there is no such thing as a fixed and easily recognized boundary between semiospheres. Your comment about the boundary really being some sort of  “permeable membrane” is one I agree with. I don’t think from what I have read that Lotman would disagree with you on that point, as he describes the boundary in the following way:

Insofar as the space of the semiosphere has an abstract character, its boundary cannot be visualized by means of concrete imagination. Just as in mathematics the border represents a multiplicity of points, belonging simultaneously to both the internal and external space, the semiotic border is represented by the sum of bilingual translatable “filters”, passing through which the text is translated into another language … situated outside the given semiosphere. (“On the Semiosphere”, Juri Lotman)

I do like his biosphere analogy, and it brings to mind another possible analogy that might be useful, namely that of an “ecosystem”. I’ll be looking into that soon. My notion (and as always it is a laypersons notion) is that the problem of description of a particular ecosystem presents the same puzzle as the identification and description of a semiosphere.

What’s in the ecosystem and what’s outside of it? If we’re talking about a salt marsh ecosystem, for example, where does the geographic border lie? Which creatures are part of the system and which ones are strangers to it (just travelling through)?

If a predator in the woods abutting the salt marsh happens to occasionally eat a creature from the salt marsh when they stray too far from home, does that make the predator part of the salt marsh ecosystem or not? What if they primarily eat forest critters? What if they primarily eat salt marsh critters? What if they eat equal amounts of forest and salt marsh critters?

What we see in this example is that the predator is an edge creature relative to the defined forest and salt marsh ecosystems. When we make this story about a particular individual creature, then whether the predator is in one or another ecosystem is dependent on how that ecosystem has been defined generally.

To the creature, the distinction is meaningless. It lives in both places, walks ground that is sometimes wooded and solid and sometimes muddy and loose. It eats what it can catch from either place. From the predator’s individual point of view, the world consists of bits of both ecosystems. In fact, from their point of view they probably would not recognize that they lived on the margins of two very different environments.

Now add to this the two individual prespectives of a salt marsh prey creature and a forest prey creature. Their typical experience, understanding and adaptation is of the more frequently encountered predators in their milieu. In fact they may have evolved special protections or strategies for foiling these common dangers.

If our predator is mostly a forest feeder, then the forest prey may be well adapted to avoid it, while the salt marsh prey may not. The salt marsh prey in this case may not understand or recognize the danger at all. Or else, if the individual salt marsh creature had spent some time with his pals at the edge of the forest, he may ultimately recognize the predator, although it might take a few moments to react.

Look, an individual creature does not typically experience a disjointed reality. The transition from forest to salt marsh is gradual (but recognizable). Our predator may have a worldview that includes elements of both the forest and the salt marsh. By virtue of this combined perception, the predator may experience what would be considered neither salt marsh nor forest, but the combination and unification of this edge reality.

To turn this back into a discussion of semantics, then…

If we equate our edge creature to a person with knowledge of two different domains (yourself, for example), then we get the same questions: which domain is that person a member of? If he primarily communicates in American vernacular but occasionaly uses Irish idioms, is he more American? If the reverse is true, perhaps he is more Irish?

In my mind the distinction is not so important to the individual, but is certainly more important to the people who share more of the “core” and less of the “periphery” (as Lotman described it) of various spheres. But these distinctions are relative, and what is “core” to one person would be “periphery” to another.

Such an edge person can “digest” and understand many aspects of the “core” of each of the semiospheres they experience. But by virtue of their experiences at the edge between, they may not by fully aware of the all aspects of those cores. Their experience of the semiosphere (as we saw with our predator example) is also not disjointed, but forms a seamless continuum. also does not lack for complexity or meaning, even though it does not represent either core. In fact, the experience of the boundary will be exactly the same in form (but not in content) as the experience of someone else in the center of a semiosphere.

I also think that in the case of the semiosphere, as with our ecosystem example, the “boundary” or “permeable membrane” is generated only by the existence of individual creatures who bridge it and cross freely between the domains. In the case of human communication, however, I think we all are “bridging” these gaps all the time, so much so that we don’t usually experience the shift until we are reminded of them by an unfamiliar word. The mere fact of a term’s unfamiliarity proves the case of a boundary condition for the individual.

Living in My Own, Personal Semiosphere

I am sure I’m not getting this right when I read these seminal papers on the “semiosphere”, beginning with Juri Lotman’s “On The Semiosphere” (Sign Systems Studies 33.1. 2005).  I have to admit that the text has me confused a bit. On the one hand, Juri defines the semiosphere as an analog to the biosphere, a large, all pervading expanse of interconnected life on our planet. On the other hand, as he describes its features (what it is and what it is not), he describes examples of something which can be quite a bit smaller than the entirety of semantic discourse in the world. This includes the semiospheres of countries, language groups, and professional practitioners.

In other words, what I would call contexts.

Taking from this the idea that a semiosphere represents the sum total aggregate of the symbollic space around this context, I had a vision of myself, walking with a sphere of communication techniques and examples (language, art, gesture, expression) floating about me. This cloud represented not just anything that I had ever said or written (or otherwise communicated) but included the entirety of what I might ever say, or be able to say.

The sum total of everything I will ever be able to communicate.

The sum total of everything I will ever be able to communicate.

And then I thought of two of us coming together, each with our own spheres of semiotics, including personal and community symbols, and an ability to recognize and quickly adapt to contexts known to us. I imagine the interplay of our own personal semiospheres, one to the other, as we begin to try to communicate.

Having brought with ourselves the entirety of our communicative arsenol, we lob niceties and platitudes at each other, then observe which ones hook together in the shared semiotic space surrounding us. Not all of our personal spheres can be fit together – like oil and water, even if we give them both the name “liquid” cannot mix.

On first encounter, we may only recognize “the weather” and “the place” as subjects shared and in common. But as we meet over time, and we remember what connections we made before, we build the “bridge” of communication between us, and this bridge becomes our starting point for subsequent communication  (in other words, our context).

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