We began by reviewing the features of funny shaggy dog stories that you identified last week (and in your analysis for today) - and then we ranked them. They came out - in order of importance- as follows.
1. Punchline
- audeince connection to the punchline in terms of familiarity (what they like) and understanding
- play on words
2. Development
- ridiculous use of terms in the punchline
- image/audience connection to the image + ridiculousness (surprise) of the characterization
- length (the longer the funnier)
3. level of violence (and who wins = funnier when the "bad" guy/force wins)
When I summed up your preferences/predictions the table looked like this:
1 (the string 242 words) 6/4/-/-
2. (hollandiase 147 words) 1/1/8/2
3. (Ghandi) 64 words 1/3/1/7
4. (lawyer = 238 words) 4/4/3/1
These rankings suggest that length is a good predictor (though not the only factor) and that while violence and punchline seem to be factors - it can be hard to tell who will connect to what, and we don't have enough data to say for sure what makes these jokes funny. At the same time, the length of the punchline & the number of plays on words in the punchline (the Ghandi joke has the most) doesn't necessarily seem to make a joke funnier = but the dialgog and characterization (associated with length) do seem to be a factor.
Good work on this - and I will be giving you feedback on blogs 4 & 5 as soon as I can - certainly before the end of the weekend.
Methods we have worked with so far:
visual/formal analysis (the puzzle) = useful for studying behaviors in interviews, digital writing - especially digital writing that includes images or that depends on spatial arrangement ot make meanings, learning spaces like classrooms or online sites,
oral history + interviewing (911 interviews + analysis)
textual analysis in terms of analyzing features of language and how language is used (analysis of jokes)
Inductive versus deductive analysis.
So far - we have developed theories (explanations for what is happening in our data) by first naming and classifying what is happening in the data - and then identifying what is happening in the data (looking for patterns) and then forming a "theory" about how to explain what our data show. This is an inductive approach: start by taking an exhaustive look at the data and building your theory from what you see.
For the analysis of the literacy narratives, we will try a deductive approach : where you ask a particular question and pose a particular answer with respect to the data and then use data to prove or disprove your assumption about what the data shows (see below)
In practice, most researchers move back and forth between inductive (taking an unbiased look at what the data shows and forming a question/hypothesis) and deductive (posing a theory with respect to data and seeing how well it fits) reasoning - but it is useful to know the terms. Scientific method is usually deductive; messier problems - like studies of language dynamics and human patterns for language use - are often inductive.
Literacy narratives. We spent the rest of the class talking about the sample literacy narratives = the Sample narratives 1 & 2 posted at the link to the right - and third sample handed out in class.
In class discussion you defined literacy narratives as having a focus on how the author formed his or her relationship to reading and writing.
You characterized the focus of the 3 sample literacy narratives as follows.
Sample 1. focus on struggling to choose an identity as a writer; complicated influences of family on relatioships to reading and writing
Sample 2. problems stepping into being a writer; collaborative writing; struggling to call herself a writer (when are you a real writer)
Sample 3. how the writer struggled to get her education (use writing in her education- decide who "owned" her writing); surprise in the ways education/her life turned out; persisting, family factor,
In our discussion of the three literacy narratives we characterized the last sample as more negative - including more "bad" experiences that were not completely resolved - than the other two.
Mainstream stories, dominant discourse (dominant patterns in the way language is used), and patterns for telling identity stories. This last observations connects to what language researchers and psychologists have noticed about the way individuals who are different ages tell stories about who they are. As we will read later in this course, individuals of college age tend to tell stories where they are in control and where events lead to a positive outcome. These researchers found that several forms similar to hero stories are a dominant form for college age narrators talking about traumatic experiences. Other research shows that older storytellers are not so likely to tell positive stories.
This set us up for a discussion of mainstream stories - stories that are "out there" about the way the world is. These story forms are widely used by ordinary people as they put together "explanations" (stories) for who they are and why their lives have turned out the way they are. Two important cultural stories that we identified were the American Dream and the Literacy Myth - both of which include assumptions about how and why individuals are successful
It also set us up for a discussion of social construction theories. In social construction theories, it is assumed that individuals put together their stories in terms of story forms (plot lines, characterizations, value judgments about what is right or wrong, and so on) that are "out there" in the culture. These theories assume that "mainstream" stories are easier to tell that non-mainstream stories (with values, perspectives and experiences that are either taboo or less talked about).
We will be talking about these ideas throughout the course - this was (another) introduction.
Analyzing the literacy narratives At the end of class we talked about setting up an analysis of one or more of the literacy narratives. We talked about how you might set up your analysis by asking a particular question of the data - and THEN naming (looking for) the features in the data related to your question. I'm hoping the questions are in your notes!
For next class:
Blog 6. Set up a question you might use as the focus for a research project on one or several of these literacy narratives. Identify the features relevant to your question. These features might characterize the people in the stories, the actions and interactions, the surrounding circumstances, the belief systems and assumptions and values of the people in the stories, and the outcomes. Point out how these features - and the relationships among them create an answer to your question. The more writing you post - the more feedback your classmates and I will be able to give you on your analytic process.
In class on Tuesday we will go over your posts for Blog 6. You will also do some brainstorming to find a focus for your research project. We will either meet in 313 - or I will have a computer lab room number posted here on the blog and by the door to 313.
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