32 Matching Annotations
  1. Nov 2019
    1. A large part of the ‘resources’ conversation in OER is this kind of problem. Cheaper access to books. More people using books. Nice measurable problems that can be fixed.

      Lowering costs for learning materials via OER: A complicated problem vs what Dave calls complex problems, like open pedagogies.

  2. Oct 2019
  3. Aug 2019
    1. Context notes are used as a map to a series of notes. A context note that outlines a more complex concept or broader subject, using links to other notes in the process. For example, while I’m reading a book, I build an outline of the things I find relevant, based on my highlights and notes of the book. Each of the outline’s items links to a separate note explaining the idea in more detail, and usually contains the highlighted text of the book.
  4. Jul 2019
    1. How will all educators and society have a deliberate coming together to envision equity as a guiding framework for the implementation of NGSS?

      question interrogates problem of... wow, hard for me to encapsulate in a sentence. How about: Us teachers and other stakeholders need to engage in dialogue/action around equity and NGSS in our own local connections yet be aware of and engage with other local dialogues and furthermore transform/be-transformed-by the emerging, higher level discourse. np

  5. Feb 2019
    1. The Two Sides of the H-LAM/T System

      When I view this diagram, I am reminded of Robert Rosen's Modeling Relation, an image of which is here The Modeling Relation grew out of research in Relational Biology which was the first mathematical biology to recognize that relations among organism components and between those components and the environment are key to understanding complex adaptive systems.

    2. It is the augmentation means that serve to break down a large problem in such a way that the human being can walk through it with his little steps, and it is the structure or organization of these little steps or actions that we discuss as process hierarchies.

      As I begin to read this (as I did back in 2000 when I was introduced to Doug) I begin to think in terms of reductionism as a practice in the face of problems which are highly complex, nonlinear, and which do not submit to chunking.

    1. nd often differs from his own-from that which he had yesterday, or WilJ have tomorrow.

      this stands out to me that a complex idea in the mind of one person will be fluid and different from day to day, my gut reaction was that an individual's "complex ideas" would remain rather unaltered for extended periods of time, even a lifetime. Maybe as one develops throughout life (adolescence to adulthood) one's thoughts would change, but not day to day

  6. Sep 2018
    1. Whilespatial biases may contribute to these findings,asnodes belonging to the same module tend to be anatomically colocalized [7,8],they cannot explain these effects entirely [94,95].

      Very nice review. Please note the reference [94] (Pantazatos et al.) is misplaced because they did not argue that spatial biases cannot entirely explain the putative links between CGE and functional segregation. Instead, they argued there was insufficient evidence in the original Richiardi et al. study linking elevated CGE with resting state functional networks, and that spatial biases may in fact entirely account for their findings. To describe the debate/exchange more accurately, I would suggest replacing the below sentence

      “While spatial biases may contribute to these findings, as nodes belonging to the same module tend to be anatomically colocalized [7,8], they cannot explain these effects entirely [94,95].”

      with the below paragraph:

      “Spatial biases may contribute to these findings, as nodes belonging to the same module tend to be anatomically colocalized [7,8]. Pantazatos et al. argued that these findings are entirely explained by spatial biases [94]. They showed that elevated CGE, as defined in the original Richiardi et al. study, falls monotonically as longer distance edges are removed. Moreover, they showed that 1,000 sets of randomly spaced modules all have significantly high CGE when using the same null distribution defined in the original Richiardi et al. analyses. Therefore, elevated CGE is not specifically related to functional segregation as defined by resting state functional networks, which is in direct contradiction to the main conclusion of the original Richiardi et al. study. Since randomly placed modules do not align (spatially) with any distributed pattern of functional segregation, the finding of elevated CGE may instead be attributed entirely to anatomical colocalization of the nodes within each module. In their rebuttal to [94], Richiardi et al. argue spatial biases cannot explain their findings entirely [95]. However, the authors do not offer an explanation for significantly high CGE observed for randomly spaced sets of modules, other than to note that nodes tend to be closer on average compared to when modules are defined by resting state fMRI. Future work is required to dissociate the effects of spatially proximity on relationships between CGE and spatially distributed functional networks.”

  7. Feb 2018
  8. Oct 2017
    1. Military Industrial Complex:

      1. Eisenhower has seen the consequences of this intersection of military power and his own "new look" policy

      Presidential speeches can be measured by how long we talk about them. Still one of the most referenced presidential speeches ever given.

      IRAN — Mohammed Mossafegh (1951–1954)

      • First military Coup during CIA golden age
      • US tells Shah Mohammad Reza Pahlavi (1941–1979) that they will take over the country unless he overthrows Mossafegh.
      • For 20+ years we supported a dictator who murdered his own people
      • Any nation state has the option to buy out foreign companies

      Guatemala — Jacobo Arbenz Guzman (1951–1954)

      • Democratically elected leader, called for Progressive Reform (second President to do so)
      • Nationalizing land (US decided it looked like Communism)
      • Guzman runs into problems with the United Fruit Company, who had been cheating on their taxes, undervaluing their land prices. Government seeks to purchase land to nationalize it, and wants to buy it for the price that the UFC valued their land for.
      • UFC and US Government set up a military Coup. Using radio broadcast propaganda, pretending that an army is ravaging the countryside. Guzman believes the propaganda and flees. We set up a dictator.
  9. May 2017
    1. The dance (or, as I prefer to call it, the complex ecolo

      This is an interesting move in terms of form. Hayles herself is the one who introduced the term "dance" and then immediately amends it parenthetically to comment that she prefers the term "complex ecology." I'm not sure why she chose to leave both of those thoughts in, but I like it.

  10. Apr 2017
    1. This is why people can play the piano with their fingers but not with their toes.

      That does not really explain why there are very talented musicians that have limb defects, but I suppose that similar to a blind person being able to hear better, their brains adjust (like complex-adaptive systems do) and reassign a new input-element (e.g. the feet) to a left-over motoric system(e.g. the hands).

  11. Mar 2017
    1. There may well be a dominant reading, but this can erode over time if the “interpretive community” (Fish 1980) to which it speaks changes or the message lost entirely if that com-munity is decisively disrupted or displaced.14
  12. Oct 2016
    1. Oklahoma Correctional Industries; workers scan the original photos and prepare metadata

      We can make the argument here that the University of North Texas, the Oklahoma Historical Society, and the Ethics in Journalism Foundation support de facto slave labor. Let's be honest here: "workers" = "prisoners"

  13. Jun 2016
    1. And now we’re besties again.

      I can relate. I have deep respect for AK but often find myself flipping back and forth between strong agreement and feeling somewhat off-put by what he writes. That seems like a healthier relationship to have with any public intellectual though than 100% agreement 100% of the time. I'm so glad his writing exists in the world and I'm glad yours does too. Seems like this kind of layered relationship is just part of dealing with complex systems. :-)

  14. Jan 2016
    1. Stupid models are extremely useful. They are usefulbecause humans are boundedly rational and because language is imprecise. It is often only by formalizing a complex system that we can make progress in understanding it. Formal models should be a necessary component of the behavioral scientist’s toolkit. Models are stupid, and we need more of them.

      Formal models are explicit in the assumptions they make about how the parts of a system work and interact, and moreover are explicit in the aspects of reality they omit.

      -- Paul Smaldino

    2. Microeconomic models based on rational choice theory are useful for developing intuition, and may even approximate reality in a fewspecial cases, but the history of behavioral economics shows that standard economic theory has also provided a smorgasbord of null hypotheses to be struck down by empirical observation.
    3. Where differences between conditions are indicated, avoid the mistake of running statistical analyses as if you were sampling from a larger population.

      You already have a generating model for your data – it’s your model. Statistical analyses on model data often involve modeling your model with a stupider model. Don’t do this. Instead, run enough simulations to obtain limiting distributions.

    4. A model’s strength stemsfromits precision.

      I have come across too many modeling papers in which the model – that is, the parts, all their components, the relationships between them, and mechanisms for change – is not clearly expressed. This is most common with computational models (such as agent-based models), which can be quite complicated, but also exists in cases of purely mathematical models.

    5. However, I want to be careful not to elevate modelers above those scientists who employ other methods.

      This is important for at least two reasons, the first and foremost of which is that science absolutely requires empirical data. Those data are often painstaking to collect, requiring clever, meticulous, and occasionally tedious labor. There is a certain kind of laziness inherent in the professional modeler, who builds entire worlds from his or her desk using only pen, paper, and computer. Relatedly, many scientists are truly fantastic communicators, and present extremely clear theories that advance scientific understanding without a formal model in sight. Charles Darwin, to give an extreme example, laid almost all the foundations of modern evolutionary biology without writing down a single equation.

    6. Ultimately,the theory has been shown to be incorrect, and has been epistemically replaced by the theory of General Relativity. Nevertheless, the theory is able to make exceptionally good approximations of gravitational forces –so good that NASA’s moon missions have relied upon them.

      General Relativity may also turn out to be a "dumb model". https://twitter.com/worrydream/status/672957979545571329

    7. Table 1.Twelve functions served by false models. Adapted with permissionfrom Wimsatt

      Twelve good uses for dumb models, William Wimsatt (1987).

    8. To paraphrase Gunawardena (2014), a model is a logical engine for turning assumptions into conclusions.

      By making our assumptions explicit, we can clearly assess their implied conclusions. These conclusions will inevitably be flawed, because the assumptions are ultimately incorrect or at least incomplete. By examining how they differ from reality, we can refine our models, and thereby refine our theories and so gradually we might become less wrong.

    9. the stupidity of a model is often its strength. By focusing on some key aspects of a real-world system(i.e., those aspectsinstantiated in the model), we can investigate how such a system would work if, in principle, we really couldignore everything we are ignoring. This only sounds absurd until one recognizes that, in our theorizing about the nature of reality –both as scientists and as quotidianhumans hopelessly entangled in myriad webs of connection and conflict –weignore thingsall the time.
    10. The generalized linear model, the work horse ofthe social sciences, models data as being randomly drawn from a distribution whose mean varies according to some parameter. The linear model is so obviously wrong yet so useful that the mathematical anthropologist Richard McElreathhas dubbed it “the geocentric model of applied statistics,”in reference to the Ptolemaic model of the solar system that erroneously placed the earth rather than the sun at the center but nevertheless produced accurate predictions of planetary motion as they appeared in the night sky(McElreath 2015).

      A model that approximates some aspect of reality can be very useful, even if the model itself is flat-out wrong.

      But on the other hand, we can't accept approximation of reality as hard proof that a model is correct.

    11. Unfortunately, my own experience working with complex systems and working among complexity scientistssuggests that we are hardly immune to such stupidity. Consider the case of Marilyn Vos Savantand the Monty Hall problem.

      Many people, including some with training in advanced mathematics, contradicted her smugly. But a simple computer program that models the situation can demonstrate her point.

      2/3 times, your first pick will be wrong. Every time that happens, the door Monty didn't open is the winner. So switching wins 2/3 times.

      http://marilynvossavant.com/game-show-problem/

    12. Mitch Resnick, in his book Turtles, Termites, and Traffic Jams, details his experiences teaching gifted high school students about the dynamics of complex systems using artificial life models (Resnick 1994). He showed them how organized behavior could emerge when individualsresponded only to local stimuli using simple rules, without the need for a central coordinating authority. Resnick reports that even after weeks spent demonstrating the principles of emergence,using computer simulations that the students programmed themselves, many students still refused to believe that what they were seeing could really work without central leadership.
  15. Apr 2015
    1. First, the domain is a poor candidate because the domain of all entities relevant to neurobiological function is extremely large, highly fragmented into separate subdisciplines, and riddled with lack of consensus (Shirky, 2005).

      Probably a good thing to add to the Complex Data integration workshop write up

  16. Nov 2013