RE: Language and memes

From: Lawrence de Bivort (
Date: Tue 17 Dec 2002 - 16:43:13 GMT

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    Many thanks for the lead, Grant. I'm on the road for the next few weeks, and will follow up when I get back to Maryland. It does seem relevant. Perhaps it is time for a Washington area Memetics group...

    Cheers to all, Lawry

    > -----Original Message-----
    > From: []On Behalf
    > Of Grant Callaghan
    > Sent: Friday, November 29, 2002 12:40 PM
    > To:
    > Subject: Language and memes
    > The following paper, of which I've extracted just the
    > introduction and the
    > abstract, does not use the word meme but much of what it covers has been
    > speculated about on this list over the past few months and I
    > think there may
    > be some relevance to what we've been talking about. Lawry, especially,
    > seems in a good position to check out the writers as the paper
    > originated at
    > UMD.
    > Conceptual Integration Networks
    > [Expanded web version, 10 February 2001]
    > Gilles Fauconnier
    > Department of Cognitive Science
    > University of California, San Diego
    > Mark Turner
    > Department of English and Program in Neuroscience and Cognitive Science
    > University of Maryland
    > The web page for research on conceptual integration is
    > Published in Cognitive Science, 22(2) 1998, 133-187.
    > Copyright © Cognitive Science Society, Inc. Used by permission.
    > Abstract
    > Conceptual integration—"blending"—is a general cognitive
    > operation on a par
    > with analogy, recursion, mental modeling, conceptual categorization, and
    > framing. It serves a variety of cognitive purposes. It is
    > dynamic, supple,
    > and active in the moment of thinking. It yields products that frequently
    > become entrenched in conceptual structure and grammar, and it
    > often performs
    > new work on its previously entrenched products as inputs.
    > Blending is easy
    > to detect in spectacular cases but it is for the most part a routine,
    > workaday process that escapes detection except on technical
    > analysis. It is
    > not reserved for special purposes, and is not costly.
    > In blending, structure from input mental spaces is projected to a
    > separate,
    > "blended" mental space. The projection is selective. Through completion
    > and elaboration, the blend develops structure not provided by the
    > inputs.
    > Inferences, arguments, and ideas developed in the blend can have
    > effect in
    > cognition, leading us to modify the initial inputs and to change
    > our view of
    > the corresponding situations.
    > Blending operates according to a set of uniform structural and dynamic
    > principles. It additionally observes a set of optimality principles.
    > Contents
    > I. Introduction
    > II. An illustration
    > III. The
    > network model
    > of conceptual integration
    > IV. Applications
    > V.
    > Advanced aspects
    > of the network model
    > VI. Optimality
    > principles
    > VII. Additional
    > dimensions of conceptual integration
    > VIII. Summary
    > and further
    > results
    > IX. Conclusion
    > I. Introduction
    > Much of the excitement about recent work on language, thought, and action
    > stems from the discovery that the same structural cognitive
    > principles are
    > operating in areas that were once viewed as sharply distinct and
    > technically
    > incommensurable. Under the old view, there were word meanings, syntactic
    > structures, sentence meanings (typically truth-conditional),
    > discourse and
    > pragmatic principles, and then, at a higher level, figures of speech like
    > metaphor and metonymy, scripts and scenarios, rhetoric, forms of
    > inductive
    > and deductive reasoning, argumentation, narrative structure, etc. A
    > recurrent finding in recent work has been that key notions,
    > principles, and
    > instruments of analysis cut across all these divisions and in
    > fact operate
    > in non-linguistic situations as well. Here are some of them:
    > Frames structure our conceptual and social life. As shown in the work of
    > Fillmore, Langacker, Goldberg, and others, they are also, in their most
    > generic, and schematic forms, a basis for grammatical
    > constructions. Words
    > are themselves viewed as constructions, and lexical meaning is an
    > intricate
    > web of connected frames. Furthermore, although cognitive framing is
    > reflected and guided by language, it is not inherently
    > linguistic. People
    > manipulate many more frames than they have words and constructions for.
    > Analogical mapping, traditionally studied in connection with reasoning,
    > shows up at all levels of grammar and meaning construction, such as the
    > interpretation of counterfactuals and hypotheticals, category formation ,
    > and of course metaphor, whether creative or conventional.
    > Reference points, focus, viewpoints, and dominions are key
    > notions not only
    > at higher levels of narrative structure, but also at the seemingly
    > micro-level of ordinary grammar, as shown convincingly by Langacker 1993,
    > Zribi-Hertz 1989, Van Hoek 1997, Cutrer 1994, among others.
    > Connected mental spaces account for reference and inference
    > phenomena across
    > wide stretches of discourse, but also for sentence-internal multiple
    > readings and tense/mood distributions. Mappings at all levels operate
    > between such spaces, and like frames they are not specifically
    > linguistic.
    > (Fauconnier 1997, Dinsmore 1991, Cutrer 1994, Fauconnier and Sweetser,
    > 1996).
    > Connectors and conceptual connections also operate at all levels, linking
    > mental spaces and other domains for coreference, for metonymy (Nunberg
    > 1978), and for analogy and metaphor (Turner 1991, Sweetser 1990).
    > There are other notions that apply uniformly at seemingly
    > different levels,
    > such as figure/ground organization (Talmy 1978), profiling, or pragmatic
    > scales.Running through this research is the central cognitive scientific
    > idea of projection between structures. Projection connects frames to
    > specific situations, to related frames, and to conventional scenes.
    > Projection connects related linguistic constructions. It connects one
    > viewpoint to another and sets up new viewpoints partly on the
    > basis of old.
    > It connects counterfactual conceptions to non-counterfactual
    > conceptions on
    > which they are based. Projection is the backbone of analogy,
    > categorization, and grammar.
    > In the present study, we show that projection typically involves
    > conceptual
    > integration. There is extensive previous research on varieties of
    > projection, but not on conceptual integration. Empirical
    > evidence suggests
    > that an adequate characterization of mental projection requires a
    > theory of
    > conceptual integration. We propose the basis for such a theory and argue
    > that conceptual integration—like framing or categorization—is a basic
    > cognitive operation that operates uniformly at different levels of
    > abstraction and under superficially divergent contextual
    > circumstances. It
    > also operates along a number of interacting gradients. Conceptual
    > integration plays a significant role in many areas of cognition. It has
    > uniform, systematic properties of structure and dynamics.
    > The nature of mapping between domains has enjoyed sustained
    > attention as a
    > central problem of cognitive science, and voluminous literatures have
    > developed in this area, including studies by those who call their subject
    > "analogy" or "similarity" (e. g., Hofstadter 1985, 1995a, Mitchell 1993,
    > French 1995, Keane, Ledgeway, and Duff 1994; Holyoak and Thagard, 1989,
    > 1984; Forbus, Gentner, and Law, 1994; Gentner 1983, 1989; Holland,
    > Holyoak, Nesbett, and Thagard, 1986), studies by those who call their
    > subject "metaphor" (e.g., Lakoff and Johnson 1980; Lakoff and
    > Turner 1989;
    > Sweetser 1990; Turner 1987; Indurkhya 1992; Gibbs 1994) and
    > studies that
    > consider cross-domain mapping in general (e.g., Fauconnier 1997, Ortony
    > 1979a, 1979b, Glucksberg and Keysar 1990, Turner 1991).
    > Our immediate goal is not to take a stand on issues and problems of
    > cross-space mappings. Those issues are many and the debates over
    > them will
    > continue and will be further enriched, we hope, by taking blending into
    > consideration. What we will be suggesting is that models of cross-space
    > mapping do not by themselves explain the relevant data. These
    > data involve
    > conceptual integration and multiple projections in ways that have
    > typically
    > gone unnoticed. Cross-space mapping is only one aspect of conceptual
    > integration, and the existing body of research on the subject overlooks
    > conceptual integration, which it is our intention to foreground
    > and analyze
    > here. As we move through the data that crucially involves both
    > cross-space
    > mapping and conceptual integration, we will remark that much of it is
    > neither metaphoric nor analogical. [1]
    > We take it as an established and fundamental finding of cognitive science
    > that structure mapping and metaphorical projection play a central role in
    > the construction of reasoning and meaning. In fact, the data we analyze
    > shows that such projections are even more pervasive than previously
    > envisioned. Given the existence and key role of such mappings,
    > our focus is
    > on the construction of additional spaces with emergent structure, not
    > directly available from the input domains.
    > We also rely on another fundamental finding of cognitive science, the
    > capacity for mental simulation, as demonstrated in Johnson-Laird (1983),
    > Kahneman (1995), Grush (1995), Schwartz and Black (1996), Barsalou (1996)
    > among others. In our analysis, the simulation capacity assists in the
    > on-line elaboration of blended spaces ("running the blend").
    > There is the
    > added twist that simulation can operate on mental spaces which
    > need not have
    > potential real world reference.
    > Our methodology and argumentation take the following form. Since the
    > cognitive process of conceptual integration has been largely
    > overlooked, it
    > is useful to give evidence for its operation in a wide variety of areas.
    > Since conceptual integration has uniform structural and dynamic
    > properties,
    > it is important to reveal this uniformity behind the appearance of
    > observational and functional diversity. We proceed analytically and
    > empirically, by showing that central inferences, emotions, and
    > conceptualizations, not explained in currently available frameworks, are
    > accounted for elegantly by the conceptual integration model. The
    > argumentation often takes the following specific form: a
    > particular process
    > of meaning construction has particular input representations; during the
    > process, inferences, emotions and event-integrations emerge which cannot
    > reside in any of the inputs; they have been constructed
    > dynamically in a new
    > mental space—the blended space—linked to the inputs in systematic
    > ways. For
    > example, "They dug their own financial grave" draws selectively from
    > different and incompatible input frames to construct a blended space that
    > has its own emergent structure and that provides central inferences. In
    > this case, the blended space has become conventional.
    > The diversity of our data (of which only a small sample appears in the
    > present paper) is necessary to support our claim for generality. (In
    > showing that cell division is a basic process, it is necessary to
    > study it
    > for many kinds of cells. In arguing that natural selection is a general
    > principle, it is necessary to exemplify it for widely different organisms
    > and species.) In arguing that conceptual integration is a basic
    > cognitive
    > operation, we must show that it operates in many different kinds of cases.
    > Conceptual blending is not a compositional algorithmic process
    > and cannot be
    > modeled as such for even the most rudimentary cases. Blends are not
    > predictable solely from the structure of the inputs. Rather, they are
    > highly motivated by such structure, in harmony with independently
    > available
    > background and contextual structure; they comply with competing
    > optimality
    > constraints discussed in section VI, and with locally relevant functional
    > goals. In this regard, the most suitable analog for conceptual
    > integration
    > is not chemical composition but biological evolution. Like analogy,
    > metaphor, translation, and other high-level processes of meaning
    > construction, integration offers a formidable challenge for explicit
    > computational modeling.
    > Special cases of conceptual blending have been discussed insightfully by
    > Koestler (1964), Goffman (1974), Talmy (1977), Fong (1988), Moser and
    > Hofstadter (ms.), and Kunda, Miller and Clare (1990). Fauconnier
    > (1990) and
    > Turner (1991) also contain analyses of such phenomena. All these
    > authors,
    > however, take blends to be somewhat exotic, marginal manifestations of
    > meaning. We will show here that the process is in fact central, uniform,
    > and pervasive.
    > The data and analysis we consider here suggest many psychological and
    > neuropsychological experiments (Coulson 1997), but in the present
    > work our
    > emphasis is on the understanding of ecologically valid data. Research on
    > meaning, we suggest, requires analysis of extensive ranges of data, which
    > must be connected theoretically across fields and disciplines by general
    > cognitive principles.
    > We start our report with an effective but somewhat idealized example of
    > blending, in order to illustrate the issues and terminology. We then
    > outline the general process of conceptual integration and the systematic
    > dynamic properties of blends. We work through some case-studies in a
    > variety of areas. Section VI presents the competing optimality
    > principles
    > under which conceptual integration operates.
    > Grant
    > _________________________________________________________________
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    > ===============================================================
    > This was distributed via the memetics list associated with the
    > Journal of Memetics - Evolutionary Models of Information Transmission
    > For information about the journal and the list (e.g. unsubscribing)
    > see:

    =============================================================== This was distributed via the memetics list associated with the Journal of Memetics - Evolutionary Models of Information Transmission For information about the journal and the list (e.g. unsubscribing) see:

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