205 Matching Annotations
  1. Last 7 days
    1. The term comes from Niklaus Luhmann, a German autodidact and famously prolific academic sociologist. Similar techniques were developed independently by Nabokov and Prisig, among others.


      Wow. Even in the pinned post on r/Zettelkasten, they propagate the myth by implication that Luhmann invented the Zettelkasten.

      They also suggest that Nabokov and Pirsig independently developed similar techniques rather than that it was a commonplace (excuse the pun) pattern in the broader culture.

  2. Jun 2022
    1. As my colleague Robin Paige likes to say, we are also social beings in a social world. So if we shift things just a bit to think instead about the environments we design and cultivate to help maximize learning, then psychology and sociology are vital for understanding these elements as well.

      Because we're "social beings in a social world", we need to think about the psychology and sociology of the environments we design to help improve learning.

      Link this to: - Design of spaces like Stonehenge for learning in Indigenous cultures, particularly the "stage", acoustics (recall the ditch), and intimacy of the presentation. - research that children need face-to-face interactions for language acquisition

    1. https://www.insidehighered.com/blogs/learning-innovation/why-%E2%80%98how-humans-learn%E2%80%99-book-i%E2%80%99ve-been-waiting

      How Humans Learn: The Science and Stories Behind Effective College Teaching by Joshua R. Eyler #books/wanttoread<br /> Published in March 2018

      Mentioned at the [[Hypothesis Social Learning Summit - Spotlight on Social Reading & Social Annotation]] in the chat in the [[Social Annotation Showcase]]

    2. It will be interesting to see where Eyler takes his scholarship post-COVID. I’ll be curious to learn how Eyler thinks of the intersection of learning science and teaching practices in an environment where face-to-face teaching is no longer the default.

      Face-to-face teaching and learning has been the majority default for nearly all of human existence. Obviously it was the case in oral cultures, and the tide has shifted a bit with the onset of literacy. However, with the advent of the Internet and the pressures of COVID-19, lots of learning has broken this mold.

      How can the affordances of literacy-only modalities be leveraged for online learning that doesn't include significant fact-to-face interaction? How might the zettelkasten method of understanding, sense-making, note taking, and idea generation be leveraged in this process?

    3. For college professors, I think the critical contribution of How Humans Learn is that good teaching is constructed, not ordained.

      "...good teaching is constructed, not ordained."

  3. May 2022
  4. Apr 2022
    1. ReconfigBehSci. (2020, November 5). @ToddHorowitz3 2/2 so I would prefer to treat this as an opportunity for empirical observation and learning. Evaluation should focus on trying to assess actual contribution, not a priori judgments. [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1324367278352355330

    1. (7) ReconfigBehSci on Twitter: “@ToddHorowitz3 probably- and I think there are many interesting questions around why he is there and whether he should be there. But to answer those properly, looking at the performance of the model seems important and interesting to me- that is all I am saying” / Twitter. (n.d.). Retrieved March 6, 2021, from https://twitter.com/SciBeh/status/1324389147050569734

    1. std::move_if_noexcept will return a movable r-value if the object has a noexcept move constructor, otherwise it will return a copyable l-value. We can use the noexcept specifier in conjunction with std::move_if_noexcept to use move semantics only when a strong exception guarantee exists (and use copy semantics otherwise).

      如果在 move 过程中遇到异常,有什么办法可以处理?

    1. std::move can be used whenever we want to treat an l-value like an r-value for the purpose of invoking move semantics instead of copy semantics.

      std::move 在什么情况下可以使用?

    1. First, r-value references extend the lifespan of the object they are initialized with to the lifespan of the r-value reference (l-value references to const objects can do this too). Second, non-const r-value references allow you to modify the r-value!

      R-value references 有什么性质非常有用?

    1. Ann Bergin writes (in her diary with respect to [[Zoom Session 1 for The Extended Mind]]):

      She [Mary Douglas] argues that ring composition is an enabling constraint, both for storytelling and interpretation. Douglas mentions a form of parallelism in divination in ancient China based upon the symmetrical markings on either side of a turtle shell.

      This sounds quite similar to me to the work in Bascom's Sixteen Cowries which Lynne Kelly summarizes in The Memory Code when talking about West African divination systems (particularly the Yoruba) using seeds, nuts, and cowrie shells and songs which memorized songs are sung based on the outcomes of tossing these objects.

      Is there in fact a link between these storytelling/song systems? Are they functioning roughly the same way? Is there a level of recombination or statistical chance in the ring composition systems Douglas is describing? Are they similar without the combinatorial portions?


      W.R. Bascom, Sixteen Cowries: Yoruba divination from Africa to the New World, Bloomington, IN: Indiana University Press, 1980.

  5. Mar 2022
    1. En somme, les études sur la communication des élèves atteints d’autisme permettent de mettre en évidence l’importance d’un contexte riche en stimulations appropriées (sons et images), mais également une évidente « stabilité » de l’information à décoder, le suivi des émotions des personnages, le rôle de l’imitation dans les apprentissages. Ces résultats encouragent donc l’usage d’outils informatiques adéquats pour améliorer la communication sociale chez les enfants atteints d’autisme.

      L'association de deux sujets qui n'ont pas de corrélation vérifiéé, revient dans la conclusion en contradiction avec la conclusion de l'étude de Ramdoss, S et al.

    2. Nous allons montrer par une courte analyse de quelques études l’impact du travail éducatif informatisé dans l’apprentissage de la communication sociale chez des enfants atteints d’autisme.

      En contradiction avec l'hypothèse :

      Results suggest that CBI should not yet be considered a researched-based approach to teaching communication skills to individuals with ASD. However, CBI does seem a promising practice that warrants future research. Les résultats suggèrent que le CBI ne devrait pas encore être considéré comme un approche fondée sur la recherche pour enseigner les compétences en communication aux personnes ayant Troubles du Spectre Autistique. Cependant, le CBI semble être une pratique prometteuse qui justifie des recherches futures.

    3. L’imitation et l’influence du jeu interactif sont bien mises en évidence dans une étude de Orit Hetzroni et Juman Tannous, de la Faculté des Sciences de l’éducation de l’Université de Haifa (Israël)

      ==>l’échantillon de l’étude est est extrêmement limité, l’étude n’est pas répliqué et elle ne permet pas de retirer de résultats concluants

    1. For a package pkg, pkg::name returns the value of the exported variable name in namespace pkg, whereas pkg:::name returns the value of the internal variable name. The package namespace will be loaded if it was not loaded before the call, but the package will not be attached to the search path.
  6. Jan 2022
  7. Dec 2021
    1. Likewise, the filing cabinet cannot feed itself without user collaboration; indeed, without a user, the filing cabinet cannot even start its combinatory po-tential. Nevertheless, the card index is used as a true ‘communicative partner’ because it has proper autonomy. In a sense, the card index is fully dependent on and fully independent of the user. The inner structure is methodically ar-ranged so that the users, whoever they may be, can in principle use it; entries are linked so that once the combinatory potential begun, combinations repro-duce themselves and increase the available complexity in unexpected ways.34

      There is an interesting analogy here worth pursuing:

      This idea and its structure have lots of similarities to those of growth and evolution in Werner R. Loewenstein's The Touchstone of Life: Molecular Information, Cell Communication, and the Foundations of Life. What if we reframe RNA or mitochondria in the role of the filing cabinet? What emergent properties occur in these processes? What do these processes have in common?

      I need at least some shorthand idea or word for talking about the circular evolving processes of life in Loewenstein's book. Maybe evolution spirals?

      Think inputs and outputs.

  8. Nov 2021
  9. Oct 2021
  10. Sep 2021
    1. This fundamental truth (expressed in economic notation as r > g, or "return on capital is greater than economic growth") means that "meritocracy" is a lie: the richest people in a market economy aren't the people who do the best work, it's the people who started off rich.

      Thomas Piketty's r > g shows that meritocracy is a lie in that the richest people aren't the ones that do the best or most productive work, but simply those who start of rich.

    1. https://www.youtube.com/watch?v=rhgwIhB58PA

      Learning styles have been debunked.

      Learning styles: V.A.R.K. model originated by Neil Flemiing stands for:

      • visual
      • auditory
      • reading/writing
      • kinesthetic


      Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological science in the public interest, 9(3), 105-119. — https://ve42.co/Pashler2008

      Willingham, D. T., Hughes, E. M., & Dobolyi, D. G. (2015). The scientific status of learning styles theories. Teaching of Psychology, 42(3), 266-271. — https://ve42.co/Willingham

      Massa, L. J., & Mayer, R. E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style?. Learning and Individual Differences, 16(4), 321-335. — https://ve42.co/Massa2006

      Riener, C., & Willingham, D. (2010). The myth of learning styles. Change: The magazine of higher learning, 42(5), 32-35.— https://ve42.co/Riener2010

      Husmann, P. R., & O'Loughlin, V. D. (2019). Another nail in the coffin for learning styles? Disparities among undergraduate anatomy students’ study strategies, class performance, and reported VARK learning styles. Anatomical sciences education, 12(1), 6-19. — https://ve42.co/Husmann2019

      Snider, V. E., & Roehl, R. (2007). Teachers’ beliefs about pedagogy and related issues. Psychology in the Schools, 44, 873–886. doi:10.1002/pits.20272 — https://ve42.co/Snider2007

      Fleming, N., & Baume, D. (2006). Learning Styles Again: VARKing up the right tree!. Educational developments, 7(4), 4. — https://ve42.co/Fleming2006

      Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional method: Effects on comprehension. Journal of educational psychology, 107(1), 64. — https://ve42.co/Rogowskyetal

      Coffield, Frank; Moseley, David; Hall, Elaine; Ecclestone, Kathryn (2004). — https://ve42.co/Coffield2004

      Furey, W. (2020). THE STUBBORN MYTH OF LEARNING STYLES. Education Next, 20(3), 8-13. — https://ve42.co/Furey2020

      Dunn, R., Beaudry, J. S., & Klavas, A. (2002). Survey of research on learning styles. California Journal of Science Education II (2). — https://ve42.co/Dunn2002

  11. Aug 2021
    1. We think R is a great place to start your data science journey because it is an environment designed from the ground up to support data science. R is not just a programming language, but it is also an interactive environment for doing data science. To support interaction, R is a much more flexible language than many of its peers. This flexibility comes with its downsides, but the big upside is how easy it is to evolve tailored grammars for specific parts of the data science process. These mini languages help you think about problems as a data scientist, while supporting fluent interaction between your brain and the computer.
  12. Jul 2021
    1. Why do 87% of data science projects never make it into production?

      It turns out that this phrase doesn't lead to an existing research. If one goes down the rabbit hole, it all ends up with dead links

    1. David Fisman. (2021, July 8). Fascinating new preprint on delta vs older variants in well-investigated outbreaks in China. Viral load for delta is 3 log higher, and latent period is shorter too (estimate is 4 days vs 6 days). This may explain much higher R estimates which may be due to elevated viral load [Tweet]. @DFisman. https://twitter.com/DFisman/status/1413126886570536963

  13. Jun 2021
  14. May 2021
  15. Apr 2021
  16. Mar 2021
  17. Feb 2021
    1. unnest_wider

      unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

    2. unnest_wider

      unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

    3. unnest_wider

      unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

    4. unnest_longer

      unnest_longer( data, col, values_to = NULL, indices_to = NULL, indices_include = NULL, names_repair = "check_unique", simplify = TRUE, ptype = list(), transform = list() )

    5. unnest_longer

      unnest_longer( data, col, values_to = NULL, indices_to = NULL, indices_include = NULL, names_repair = "check_unique", simplify = TRUE, ptype = list(), transform = list() )

    6. unnest_longer

      unnest_longer( data, col, values_to = NULL, indices_to = NULL, indices_include = NULL, names_repair = "check_unique", simplify = TRUE, ptype = list(), transform = list() )

    7. unnest_wider

      unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

    8. unnest_wider

      unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

    9. hoist

      hoist( .data, .col, ..., .remove = TRUE, .simplify = TRUE, .ptype = list(), .transform = list() )

    1. Sass

      Define variables, such as colors (e.g. $primary: #337ab7) in Sass (styles.scss) then compile to css for web.

      R library "bootstraplib" built on foundation of "sass".

      Use "run_with_themer()" to get a live preview GUI for customizing bootstrap theme.

      Also, use "shinyOptions(plot.autocolors=TRUE)" at top of app to get plot outputs that respect Dark Mode.

  18. Jan 2021
  19. Dec 2020
  20. Nov 2020
    1. Let’s fit regression line to our model:

      plot() and lines() seem to plot regression lines

      • Can they be added to a ggplot?
      • Can they be used to print R2 on the plot?
  21. Oct 2020
    1. You need to get out of the habit of thinking using quotes is ugly. Not using them is ugly! Why? Because you've created a function that can only be used interactively - it's very difficult to program with it. – hadley

      Does it seem like Hadley still stands by this statement after tidy evaluation from this article <Do you need tidyeval>

    1. In practice, functional programming is all about hiding for loops, which are abstracted away by the mapper functions that automate the iteration.
    1. All figures were created using R Statistical Computing Software version 3.6.3 (R Core Team, 2020), relying primarily on the dplyr package (Wickham et al., 2015) for data manipulation and the ggplot2 package (Wickham 2016) for plotting. The code used to create each figure can be found at https://github.com/mkc9953/SARS-CoV-2-WW-EPI/tree/master.
  22. Sep 2020
    1. The neighbour‐joining tree was prepared with the R package {Ape} (Paradis, Claude, & Strimmer, 2004) and visualized using the R package {ggtree} (Yu, Smith, Zhu, Guan, & Lam, 2017).
  23. Aug 2020
  24. Jul 2020
  25. Jun 2020
    1. How to prevent the environment from being “invalidated”?Docker containers (Rocker)


    2. SAS, R, Stata, SPSS may return different results even for quantiles, or due to floating number representation! The results should be maximally close to each other, but what about resampling methods (SAS and R gives different random numbers for the same seed)?

      Different results between SAS, R, Stata, SPSS

    3. 99.9% open-source. 0.1% is licensed (free for non-commercial use)

      License of libraries in R

    4. Status of R on the Clinical Research market
      • In general bioscience and academia, S ---> R has built over years its position of one of the industry standards
      • In clinical research, however, SAS reigns par excellence
      • Pharmaceutical companies, CROs and even FDA do use R “internally”.But they resist (or hesitate) to use it in submissions (to FDA)
      • Clinical Programmer or Biostatistician ≝ SAS Programmer. Period
    5. Differences in

      Differences between R and SAS:

      • origin of dates
      • default contrasts
      • used sum of squares
      • calculation of quantiles
      • generation of random numbers
      • implementation of advanced model
      • representation of floating point numbers
    6. Tospeeduptheprocesswithoutsacrificingaccuracy,theteamalsousesRevolutionRanalyticproducts

      Revolution R

    1. In most programming languages, you can only access the values of a function’s arguments. In R, you can also access the code used to compute them. This makes it possible to evaluate code in non-standard ways: to use what is known as non-standard evaluation
    1. Bail, C. A. (2016). Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media. Proceedings of the National Academy of Sciences, 113(42), 11823–11828. https://doi.org/10.1073/pnas.1607151113