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  1. Last 7 days
    1. here are several ways I havefound useful to invite the sociological imagination:

      C. Wright Mills delineates a rough definition of "sociological imagination" which could be thought of as a framework within tools for thought: 1. Combinatorial creativity<br /> 2. Diffuse thinking, flâneur<br /> 3. Changing perspective (how would x see this?) Writing dialogues is a useful method to accomplish this. (He doesn't state it, but acting as a devil's advocate is a useful technique here as well.)<br /> 4. Collecting and lay out all the multiple viewpoints and arguments on a topic. (This might presume the method of devil's advocate I mentioned above 😀)<br /> 5. Play and exploration with words and terms<br /> 6. Watching levels of generality and breaking things down into smaller constituent parts or building blocks. (This also might benefit of abstracting ideas from one space to another.)<br /> 7. Categorization or casting ideas into types 8. Cross-tabulating and creation of charts, tables, and diagrams or other visualizations 9. Comparative cases and examples - finding examples of an idea in other contexts and time settings for comparison and contrast 10. Extreme types and opposites (or polar types) - coming up with the most extreme examples of comparative cases or opposites of one's idea. (cross reference: Compass Points https://hypothes.is/a/Di4hzvftEeyY9EOsxaOg7w and thinking routines). This includes creating dimensions of study on an object - what axes define it? What indices can one find data or statistics on? 11. Create historical depth - examples may be limited in number, so what might exist in the historical record to provide depth.

  2. Aug 2022
    1. https://www.napkin.one/

      Yet another collection app that belies the work of taking, making, and connecting notes.

      Looks pretty and makes a promise, but how does it actually deliver? How much work and curation is involved? What are the outputs at the other end?

    1. http://cluster.cis.drexel.edu/~cchen/talks/2011/ICSTI_Chen.pdf

      The Nature of Creativity: Mechanism, Measurement, and Analysis<br /> Chaomei Chen, Ph.D.<br /> Editor in Chief, Information Visualization<br /> College of Information Science and Technology, Drexel University<br /> June 7‐8, 2011

      Randomly ran across while attempting to source Randall Collins quote from https://hypothes.is/a/8e9hThZ4Ee2hWAcV1j5B9w

  3. Nov 2021
  4. May 2020
  5. Jan 2019
    1. Nyhan and Reifler also found that presenting challenging information in a chart or graph tends to reduce disconfirmation bias. The researchers concluded that the decreased ambiguity of graphical information (as opposed to text) makes it harder for test subjects to question or argue against the content of the chart.

      Amazingly important double-edged finding for discussions of data visualization!