733 Matching Annotations
  1. Last 7 days
    1. This came in the context of weighing what she stood to gain and lose in leaving a staff job at BuzzFeed. She knew the worth of what editors, fact-checkers, designers, and other colleagues brought to a piece of writing. At the same time, she was tired of working around the “imperatives of social media sharing.” Clarity and concision are not metrics imposed by the Facebook algorithm, of course — but perhaps such concerns lose some of their urgency when readers have already pledged their support.

      Continuing with the idea above about the shift of Sunday morning talk shows and the influence of Hard Copy, is social media exerting a negative influence on mainstream content and conversation as a result of their algorithmic gut reaction pressure? How can we fight this effect?

    2. Matt Taibbi asked his subscribers in April. Since they were “now functionally my editor,” he was seeking their advice on potential reporting projects. One suggestion — that he write about Ibram X. Kendi and Robin DiAngelo — swiftly gave way to a long debate among readers over whether race was biological.

      There's something here that's akin to the idea of bikeshedding? Online communities flock to the low lying ideas upon which they can proffer an opinion and play at the idea of debate. If they really cared, wouldn't they instead delve into the research and topics themselves? Do they really want Taibbi's specific take? Do they want or need his opinion on the topic? What do they really want?

      Compare and cross reference this with the ideas presented by Ibram X. Kendi's article There Is No Debate Over Critical Race Theory.

      Are people looking for the social equivalent of a simple "system one" conversation or are they ready, willing, and able to delve into a "system two" presentation?

      Compare this also with the modern day version of the Sunday morning news (analysis) shows? They would seem to be interested in substantive policy and debate, but they also require a lot of prior context to participate. In essence, most speakers don't actually engage, but spew out talking points instead and rely on gut reactions and fear, uncertainty and doubt to make their presentations. What happened to the actual discourse? Has there been a shift in how these shows work and present since the rise of the Hard Copy sensationalist presentation? Is the competition for eyeballs weakening these analysis shows?

      How might this all relate to low level mansplaining as well? What are men really trying to communicate in demonstrating this behavior? What do they gain in the long run? What is the evolutionary benefit?

      All these topics seem related somehow within the spectrum of communication and what people look for and choose in what and how they consume content.

    1. Leah Keating on Twitter: “This work with @DavidJPOS and @gleesonj is now on arXiv (https://t.co/hxjZnCmKcM): ‘A multi-type branching process method for modelling complex contagion on clustered networks’ Here is a quick overview of our paper: (1/6) https://t.co/3jQ2flhk71” / Twitter. (n.d.). Retrieved July 23, 2021, from https://twitter.com/leahakeating/status/1418150117106978816

  2. Jul 2021
    1. they do not form the basis for discovery,

      I don't entirely agree with this part of the statement because the digital tools we have allow us to both view information in an entirely new way and to see connections that we couldn't have seen very readily. For example, the ability to take any written work and create a concordance of words can give us great insight that just reading the work would not have. If we wanted to see to what degree society is viewed from a male vs. female perspective between 1920 and 2020 we could analyze specific words in several pieces of literature from those time periods to see how significantly each gender is represented. If not impossible to do before digital tools, it would certainly be so laborious as to render it an insignificant goal in the scheme of humanistic inquiry. Thus we there is a basis for discovery within digital tools.

    1. Adam Kucharski on Twitter: “Useful data 👇– quick look suggests odds ratio for detection of B.1.617.2 relative to non-B.1.617.2 in vaccinated group compared to controls is 2.7 (95% CI: 0.7-10) after one dose and 1.2 (0.4-3.6) after two...” / Twitter. (n.d.). Retrieved July 2, 2021, from https://twitter.com/AdamJKucharski/status/1400443351908892675?s=20

  3. Jun 2021
    1. Bolze, A., Cirulli, E. T., Luo, S., White, S., Cassens, T., Jacobs, S., Nguyen, J., Ramirez, J. M., Sandoval, E., Wang, X., Wong, D., Becker, D., Laurent, M., Lu, J. T., Isaksson, M., Washington, N. L., & Lee, W. (2021). Rapid displacement of SARS-CoV-2 variant B.1.1.7 by B.1.617.2 and P.1 in the United States [Preprint]. Infectious Diseases (except HIV/AIDS). https://doi.org/10.1101/2021.06.20.21259195

  4. May 2021
    1. Thematic analysis was used to explore the qualitative data captured in the online survey. [22,23] describe thematic analysis as a method that seeks to find patterns, or categories, that emerge from the data, enabling the researcher to organise and provide detailed description.

      This seems like an interesting area to look into further.

      Two cited sources here:

    1. ReconfigBehSci on Twitter: ‘the SciBeh initiative is about bringing knowledge to policy makers and the general public, but I have to say this advert I just came across worries me: Where are the preceding data integrity and data analysis classes? Https://t.co/5LwkC1SVyF’ / Twitter. (n.d.). Retrieved 18 February 2021, from https://twitter.com/SciBeh/status/1362344945697308674

    1. Chen, X., Chen, Z., Azman, A. S., Deng, X., Sun, R., Zhao, Z., Zheng, N., Chen, X., Lu, W., Zhuang, T., Yang, J., Viboud, C., Ajelli, M., Leung, D. T., & Yu, H. (2021). Serological evidence of human infection with SARS-CoV-2: A systematic review and meta-analysis. The Lancet Global Health, 0(0). https://doi.org/10.1016/S2214-109X(21)00026-7

  5. Apr 2021
    1. Jeremy Faust MD MS (ER physician) on Twitter: “Let’s talk about the background risk of CVST (cerebral venous sinus thrombosis) versus in those who got J&J vaccine. We are going to focus in on women ages 20-50. We are going to compare the same time period and the same disease (CVST). DEEP DIVE🧵 KEY NUMBERS!” / Twitter. (n.d.). Retrieved April 15, 2021, from https://twitter.com/jeremyfaust/status/1382536833863651330

    1. The insertion of an algorithm’s predictions into the patient-physician relationship also introduces a third party, turning the relationship into one between the patient and the health care system. It also means significant changes in terms of a patient’s expectation of confidentiality. “Once machine-learning-based decision support is integrated into clinical care, withholding information from electronic records will become increasingly difficult, since patients whose data aren’t recorded can’t benefit from machine-learning analyses,” the authors wrote.

      There is some work being done on federated learning, where the algorithm works on decentralised data that stays in place with the patient and the ML model is brought to the patient so that their data remains private.

    1. ReconfigBehSci. ‘@sarahflecke “Reports Emerging of Rare Types of Multiple Thrombosis, Bleeding, and Thrombocytopenia .. Similar to Disseminated Intravasc. Coagulation ... in Otherwise Healthy Individuals Shortly after Receiving ..AstraZeneca ..Vaccine. These Outcomes Are Not Included in the Present Analysis.”’ Tweet. @SciBeh (blog), 2 April 2021. https://twitter.com/SciBeh/status/1377984798422077446.

  6. Mar 2021
    1. There is obvious connections between the flow paths of a use case and its test cases. Deriving functional test cases from a use case through its scenarios (running instances of a use case) is straightforward.
    2. With content based upon an action or event flow structure, a model of well-written use cases also serves as an excellent groundwork and valuable guidelines for the design of test cases
    3. Use cases are not only texts, but also diagrams, if needed.
    1. The semantic features of a word can be notated using a binary feature notation common to the framework of componential analysis.[11] A semantic property is specified in square brackets and a plus or minus sign indicates the existence or non-existence of that property.
    1. Analysis involves reaching a richer and more precise understanding of each requirement and representing sets of requirements in multiple, complementary ways.

      The most interesting point to me here is the part:

      representing sets of requirements in multiple, complementary ways.

      Please elaborate...

    1. Kaebnick, Gusmano (2018) - Making Policies about Emerging Technologies

    Tags

    Annotators

    1. Ashish K. Jha, MD, MPH. (2020, December 12). Michigan vs. Ohio State Football today postponed due to COVID But a comparison of MI vs OH on COVID is useful Why? While vaccines are coming, we have 6-8 hard weeks ahead And the big question is—Can we do anything to save lives? Lets look at MI, OH for insights Thread [Tweet]. @ashishkjha. https://twitter.com/ashishkjha/status/1337786831065264128

    1. James Whale’s Frankenstein (1931) and Bride of Frankenstein (1935) explored both the hubris of the male scientist described in Mary Shelley’s novel Frankenstein, or the Modern Prometheus (1818) as well as the repressive sexuality of Western culture. Robert Wise’s The Day the Earth Stood Still (1951) advocated for a liberal belief in the collective submission to a technocratic elite.

      I initially found this article by searching for "alien movie hubris" and the search results did not disappoint. This essay does a great job weaving several themes about creativity, automation, intelligence, biology, culture, ambition, power, delusions of grandeur, human spirituality and sexuality, and a few more I'm probably forgetting. It's definitely worthwhile reading.

    1. I had decided to write all this down because I do not know when the stinking menfish will get me. Maria, if ever you find this -my head is roaring with fever and I scarcely know what I have written

      Protista reminds me of Murakami’s works a lot, particularly of Sleep. Both stories are unclear, contain fantastical elements, and have an abrupt ending. The narrators of both are also unreliable (the narrator in Sleep has not slept for days and has drunk a lot of alcohol, while the narrator in Protista is dehydrated and malnutritioned), seem to have hallucinations, and are telling the story from some point in the future. However, for the narrator in Protista, it is completely impossible for me to tell how much of what he is telling the readers has really happened. Although in the beginning, certain parts seem believable, as the story progresses, the things the narrator is experiencing blend together and become so fantastical that one cannot even perceive them as metaphors.For example, there is the repetitive image of the red circle. On page 123, it is said that a red circle has been drawn by Maria and that it would bleed when she is in danger. Later, on page 126, such a red circle becomes the creation of the manfish that visited the narrator’s room when he was young and has been drawn so that only the narrator can see it and would bleed until the narrator goes to the manfish. Therefore, when the circle bleeds at the end on page 128, the significance that holds remains unclear to me. Another example is of Maria, who, on page 129, is described to have come back as “a fleshless skeleton”, but, on page 130, the narrator is leaving a letter for Maria, who is yet to come back. Although it is possible that the woman on page 129 is not Maria, if we presume that to be true, then it becomes unclear for whom the narrator bought a coat with silver buttons. Many other points of great confusion can be found, as well. Given the conditions the narrator is living in because of his exile (a hot, barren, dry land, where only insects seem to thrive) and the convoluted, fantastical nature of his narrative, I’m inclined to think that he has either been bitten by a disease-carrying insect, or is suffering from severe dehydration and malnutrition, and has started to hallucinate because of this. Moreover, on page 130, he mentions that his “head is roaring with fever”, and he barely knows what he has written, which further reinforces my belief in this interpretation. The narrator is possibly on the edge of dying, as well, as he uses phrases such as: “After that, the sun never came up." on page 129 and “Yesterday I met Barbara's father in the valley.” on page 130, when we know from earlier in the story that the sun is constantly drying the valley and that Barbara’s father has been dead for a long time. Overall, Protista is a very confusing story with quite an abrupt but also unsurprising ending, given the rest of the narrative (130).

    1. Cailin O’Connor. (2020, November 10). New paper!!! @psmaldino look at what causes the persistence of poor methods in science, even when better methods are available. And we argue that interdisciplinary contact can lead better methods to spread. 1 https://t.co/C5beJA5gMi [Tweet]. @cailinmeister. https://twitter.com/cailinmeister/status/1326221893372833793

  7. Feb 2021
  8. www.sciencedirect.com