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Summary of the show's topics, along with an interrupted discussion between Teh Dŭk!tər and FrEd-rEkw' on calculating the reach of the electromagnetic broadcast show and light podcast, in which is estimated to reach throughout the Local Interstellar Cloud and most of the G-Cloud.
Mood and empathy.
The existential-phenomenological concept of mood and its relation to our worldview are described, in order to introduce a way to use empathic mood-sharing to increase interpersonal understanding. Along the way, other-evaluative and see-conscious emotions are discussed, with focus on how or self-conscious emotions (like guilt and shame) reveal the pervasiveness of mood in our attitudes, perspectives, and life outcomes.
Perspective sharing and being present-at-hand.
To complete the discussion on interpersonal understanding started in the Being there segment of this episode, the cognitive component of empathy is discussed. The experience of this component, often known as perspective taking or perspective sharing, may however often at first be experienced as aversive, or problematic. Heideggarian notions of ready-to-hand and present-at-hand are used to understand this, and relatively innocuous worldviews are presented as potential sources for practicing the imaginative skills required in perspective sharing. These include guided imaginative exercises on the potential worldviews of non-human sentient beings. Anthropomorphism and Frans de Waal's anthropodenialism are discussed while doing so.
Living in Washington State, as compared to living in New York State, continued.
This episode's segment continues from the 19-10-13 show episode the themes arising from a survey among Mechanical Turk workers who live in Washington State, versus those who live in New York. Along the way, it is explained how mood is identified in a quantitative phenomenology. The segment concludes with a list of artificially generated model statements phrased according to the popularity, relationships, style, and vocabulary of the participants themselves. Along the way, it is pointed out that most quantitative approaches to natural language leave out mood-identifying information, apparently due to researcher assumptions as to what words will be important or not to the participants. The difference between phenomenology and other qualitative methods is also explained during this segment.
Here are some screenshots from the analysis. The most frequent and overrepresented words in each response are listed in descending order from left to right along the horizontal axis of the charts, while the degree each word is overprepresented (and therefore particular to the question in the group) is depicted along the vertical access (the taller the bar, the more particular a word is to the question). Bars that exceed the chart height are found at rates that exceed 100 times their typical use in everyday English.
There are more themes in the data than are depicted in these screenshots. For more detailed and colorful information, see the post about this survey on the Raven's Eye website.
On the attitude for this survey.
This survey analysis results from a quantitative phenomenology utilizing Raven's Eye. Our attitude is one that seeks to:
What results are plain English statements that express the thoughts of the participants, in the way that they are ordered and structed by the participants themselves.
On the horizons of this survey.
Any survey's results must be interpreted within the context in which is was created and analyzed. Our survey asked Mechanical Turk workers located in New York and Washington States what they thought about living in their respective state. We received 90 responses from New York state, and 86 responses from Washington state. We asked both samples to answer in their own words over the course of 2-3 sentences, what is is that they liked most about living in their part of their state. We then asked them to explain—again, over 2-3 sentences—what is is that they most disliked about living in their part of their state.
As with convenience samples in general, we should be cautious about extending the results of this survey to those beyond the group surveyed. However, by our estimates, our sample likely includes approximately 47% of the total population of Mechanical Turk workers available in Washington State during the time that the survey was available.
The cut-off threshold that we used for our analysis makes it such that our confidence in the durability of our results exceeds the total population of Mechanical Turk workers in Washington State. We are, therefore, quite confident that our results can be generally applied to this population, at least at this point in history.
Read more about the confidence in our quantitative phenomenology..
Living in Washington State.
I love the beautiful scenery.
I like that I am able to access the mountains and the ocean.
I enjoy the mild weather.
I love living in Seattle, and everything there is to do within a short drive away.
I dislike that there are too many people everywhere.
The traffic is getting worse (I-5 is clogged).
There are a lot of homeless people.
It rains very often.
The gists, or main ideas expressed by Mechanical Turk workers in Washington in response to being asked what they like about living in Washington state included: mountains, beautiful, weather, and close. City was frequently mentioned by this sample, but unlike in the New York mechanical Turk workers, among Washington Mechanical Turk workers, this concept did not reach the threshold established for inclusion in this report.
The gists, or main ideas expressed by Mechanical Turk workers in Washington in response to being asked what they dislike about living in Washington state included: people, traffic, homeless, rain, crime, and cost of living.
Living in New York State.
I like the diversity of people here from different cultures.
I love New York City; there's always something to do.
The city has good food from around the world.
There a lot of people in New York.
It is very expensive to live here.
The cost of living is very high.
The taxes are ridiculous.
The gists, or main ideas expressed by Mechanical Turk workers in New York in response to being asked what they like about living in New York State included: people, city, always, food, and different.
The gists, or main ideas expressed by Mechanical Turk workers in New York in response to being asked what they dislike about living in New York State included: people, very expensive, high cost of living, taxes, winters, and cold weather.
There are other themes in the data, but these are enough to begin reflection on the manner in which our habits and habitats shape our worldview.
Why do you think some themes, like people and cost of living, might shared across the geographically separate groups? What locally similar places or peoples might they have in common? Why do you think some themes differ? Why would traffic be a dislike in Washington, but not nearly so in New York (indeed, further down in the responses to what New Yorkers like about living in their part of their state is the transportation system). What might cause Mechanical Turk workers in Washington to like the weather, but dislike the rain? What does it mean to live in a place where the weather is nice, but the rain isn’t? Are like and dislike then not mutually exclusive? Is cost of living a concern in both places generally, or is it a worldview particular to Mechanical Turk workers?
All of these questions can be further investigated, with the method and software used in this survey, or some alternative method. They do, however, reveal the habit-begot differences in doxa between Mechanical Turk workers in New York and Washington state.
We’ll add listener survey information as the pool of respondents grows. If you’re interested in participating in a future survey, check out the survey page of this website, or create a Mechanical Turk worker account and get a chance to get paid for your response.
Our next survey asks about your nightmares and worris. Answer that survey, and then tune in to KKNW 1150 AM on Sunday October 27th, 2019 from 2:00pm - 3:00pm to hear the results!
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