The current problem lies in perceiving the world through only one division, so it would be beneficial to increase the number of divisions as much as cognitive abilities allow.
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The issue is the current state of perceiving the world through a single binary division like “Trump vs. Harris”.
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Instead, understanding things through 100 different divisions like “young generation vs. elderly”, “rural vs. urban”, “wealthy vs. middle class vs. poor” can help recognize the complexity of the current situation.
- Imagining unpacking the division summarized as “Trump vs. Harris” into multiple aspects.
- It’s akin to having a policy-based attitude of “on this issue, yes; on that issue, no.”
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Recognizing the world through 100 different divisions can prevent getting stuck in a feedback loop of one single division. It’s a shift in mindset from “eliminating divisions and echo chambers” to “creating 100 divisions and echo chambers“. In the micro, friends and foes; in the macro, smoothness, a similar discussion.
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Instead of saying “let’s stop fighting,” it’s more like “today, let’s argue about austerity vs. expansionary fiscal policy. Tomorrow, let’s argue about supporting vs. opposing selective separate surnames for married couples. The day after tomorrow, let’s argue about supporting vs. opposing military buildup.”
- It’s a positive approach to arguments.
- There’s a resemblance to Splatoon.
- Form three groups with one-third of the participants each through a pre-vote and play Three Kingdoms every week.
- Well, binary opposition seems to be more popular with the general public.
- It’s common in sports as well.
- The side that converts more from the opponent’s camp wins.
- It’s also good to easily visualize the power dynamics with a line graph.
- I see (blu3mo).
- Tricara Battle is a bit hard to understand (Haruhi).
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- This seems to align with the goal (blu3mo).
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Political positions and beliefs are often misperceived as uniform, such as “this person is conservative” or “that person is liberal,” when in fact, research on Americans shows that many individuals hold diverse political stances depending on the topic, like being liberal on abortion but conservative on immigration.
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The issue arises when news recommendations influence and potentially bias new political stances on emerging topics based on past access logs.
- Reducing Cross-Topic Political Homogenization in Content-Based News Recommendation
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Since vectors are represented by a combination of multiple components, it seems like a good idea to create various binary oppositions (takker).