Adding in the parts of message that aren’t always seen but are always intended
This section is intended to focus on the DNA and morphology of message. Colonomos’ work points interpreters towards understanding the complex modular parts of what people say, the context, demography, history and etymology: everything that frames and shapes an intended message.
Here are some bullet points/learning outcomes of which we might want to be aware:
- Semantics and message/discourse intention is a function of the speaker’s rhetorical position: where is s/he coming from? what informs this opinion or approach or message?
- How should we define affect?
- What are some ways that we can measure message intention (‘message analysis’ [Isham])? What are we looking for when we rapidly assess message intent?
Colonomos’ “blue sheet.” This description of affect defines two constituents of affect: text (form/lexical units only, no speaker intonation, expressions, gestures, etc.) and person (speaker expressions, intonation, gestures, eye behaviors). Incorporating these components from the source message helps the resulting interpretation to be more equivalent. (Don’t download this unless you lose the blue copy handed out in class.) Required
Printed in the proceedings of the 1985 RID Convention (Marina L. McIntire, ed.; Silver Spring, Maryland: RID Publications, 1986), this article by Isham is one of the seminal pieces in SL interpretation text analysis. The Patrie text talks about the importance of “illocutionary force;” c.f. Isham’s discussion of function (p. 156), affect (p. 158), and contextual force (p. 159) for additional exposition on the topic. Highly Recommended
Discussion of register in sign and spoken languages Required
Colonomos’ “orange sheet.” This diagram helps to explain where, how, and what meaning is derived in a speaker’s/signer’s discourse. All of these constituent domains add up to a speaker’s/signer’s intention. (Don’t download this unless you lose the orange copy handed out in class.)
Fantastic typology tool that defines and gives examples of the nuances of (36!) negative emotions. Seemingly helpful tool in identifying speaker intent > equivalent SL rendering and nuance.
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