Mutual Redundancies and Triple Contingencies

among Perspectives on Horizons of Meaning

Loet Leydesdorff

University of Amsterdam, Amsterdam School of Communication Research (ASCoR)

loet@leydesdorff.net; http://www.leydesdorff.net

Information, Redundancy, and the Measurement of Meaning

1. Information as uncertainty (Shannon-Weaver);

expected information; bits measurement

2. “A difference which makes a difference” (Bateson); “A distinction which makes a difference” (MacKay)

→ potentially, reduction of uncertainty; “negentropy”→ “meaningful information” for a system of reference (e.g., an observer)

→ redundancy + information = maximal information→ redundancy as the complement of information

Replace “historically excluded” with “historically not yet realized” (“adjacent others” -- Kauffman, redundancy -- Weaver);Shift of focus to the instances that could have happened.

Brooks & Wiley (1986, at p. 43): The development of the maximum information content and the historically realized information over time.

Shannon-Weaver model

Shannon (1948, p. 3): “Frequently the messages have meaning; that is they refer to or are correlated to some system with certain physical or conceptual entities. These semantic aspects of communication are irrelevant to the engineering problem.”

Warren Weaver argued that Shannon’s “bizarre” distinction between information and meaning “has so penetratingly cleared the air that one is now, for the first time, ready for a real theory of meaning” (Shannon & Weaver, 1949, p. 27).

Cultural domain; Husserl’s “cogitatum”

Correlated in “language”; codingCorrelations: sharing of meaning

Weaver (1949, p.26): “Similarly, one can imagine another box in the diagram which inserted between the information source and the transmitter, should be labeled “semantic noise”. (…) And the problem of semantic decoding must take this semantic noise into account.”

SEMANTIC NOISE

SEMANTIC NOISE

Symbolic coding of the communication

Symbolic coding of the communication

translations

Relations: transfer of information

SEMANTICS

NETWORK OF RELATIONS

(variation; retention)

VECTOR SPACE (instantiatons)HORIZONS OF MEANING

(global perspectives)

SEMANTICS

Luhmann (Husserl, Parsons, Maturana, etc.)

• Symbolically generalized codes of communication (Parsons, 1963; 1968): – For example: money, power, truth, love, etc.;

• Functional differentiation of the codes as the latent dimensions (“eigenvectors”) in the communication matrix of senders and receivers (von Foerster); (→ social system)

• Second-order dynamics because of three layers; the loops can reinforce each other into auto-catalysis (Ulanowicz; Padgett & Powell).

Layer 1Networks of communications among communicating agents:Historical proliferation of the uncertainty (entropy)

Layer 2Interactions among communications provide meaning to the communications at the supra-individual (i.e., systems) level

Layer 3Codes of communication structure the interactions, at the (next-order) “global” level

Bottom-up: Historical construction

Top-down: Evolutionary control

VARIATION; interaction;e.g. knowledge claims

ORGANIZATION; Integration

SELF-ORGANIZATION; Differentiation of Codes

Variation and selection

1. Selections at specific moments of time networks

3. Some stabilizations are selected for globalization

2. Some selections are selected for stabilization over time

→ Triple Helix of selection mechanisms

Three selection mechanisms operating upon one another can generate a positive or “negative” (missing) variation.

Two selection mechanisms operating upon each other generate a historical variation (T12 ≥ 0). Three selection mechanisms operating upon one another can generate a positive (T123 ≥ 0) or “negative” (missing) variation (T123 < 0).

Correlations are added to the relations.

Additive and subtractive color mixing

→ three different perspectives; → sharing of meaning; → generation of synergy

relationalpositional

Demand Supply

Control

innovation

Source: elaborated from Ulanowicz (2009, p. 1888).

Configurational Information: T123 = H1 + H2 + H3

– H12 – H13 – H23 + H123

→ TUIG is potentially negativeR123 < 0 : reduction of uncertainty; synergy;R123 > 0 : historical development; exploration

Mutual Information:

T12 = H1 + H2 – H12

T12 ≥ 0; always positive

R123 = T123

Loet Leydesdorff and Inga A. Ivanova, Mutual Redundancies in Inter-human Communication Systems: Steps Towards a Calculus of Processing Meaning, Journal of the Association for Information Science and Technology 65(2) (2014) 386-399:

Supply (knowledge)

Control (governance)

Demand (market)

P

Q

Ps

Pc

Pd

P and Q can be considered as vectors rotating in the three-dimensional space of supply, demand, and control; as component functions of innovation.Source: Ivanova, I. A., & Leydesdorff, L. (2014). Rotational Symmetry and the Transformation of Innovation Systems in a Triple Helix of University-Industry-Government Relations. Technological Forecasting and Social Change, 86, 143-156.

Semantic map among 56 title words connected at cosine ≥ 0.1 among 149 titles of documents in Social Science Information 2005-2009.

1. The mutual information among the three factors in the system of title words is T123 = +50.6 millibits.

No synergy among the three main factors in the historical organization of the titles in a journal.

2. When the analysis is repeated for the 187 documents that cite one of these 149 documents, T123 = –106.2 millibits;

Evolutionarily self-organization of the citing documents into three disciplinary groupings:

(i) organizational sociology; (ii) ethnology; and (iii) migration studies.

Indicator of synergy in innovation systems

• The Triple Helix provides us with a model for measuring the knowledge base of an innovation system in terms of synergies

• Three sources of variance:– geographical diversity (endowment);– technological capacity (infrastructure);– industrial structure

• Firms as units of analysis

(with Øivind Strand,) The Swedish System of Innovation: Regional Synergies in a Knowledge-Based Economy, Journal of the American Society for Information Science and Technology 64(9) (2013) 1890-1902.

Statistics Sweden: N = 1,187,421; November 2011

48.5% of the regional synergy is provided by the three metropolitan areas of Stockholm, Gothenburg, and Malmö/Lund.

Chongqing

Beijing

Shanghai

Tianjin

The distribution of 339 second-level administrative units in the PRC compared in terms of their contribution to the synergy among technology, geography, and organization. (with Ping Zhou), “Measuring the Knowledge-Based Economy of China in terms of Synergy among Technological, Organizational, and Geographic Attributes of Firms.” Scientometrics 98(3) (2014) 1703-1713.

Conclusions• Relations in the network space versus correlations in the vector space;

dyadic relations versus triple contingencies (→ “triadic closure”).

• Historical relations versus Evolutionary functions

– Historical footprints; variation; observable retention– Evolutionary differentiation; exploration of new dimensions; R > 0– possible synergy among selection mechanisms → R < 0

• The selection mechanisms are not given, but socially constructed as symbolic codes of the communication (res cogitans). They can be operationalized as evolving eigenvectors of the consecutive matrices.

• The advantages of this approach are operationalization and measurement!