Therefore, similar to Ribes et al. in their study of domain [113], the epistemic positions we propose aim to provide conceptual tools for reasoning about different styles of organizing creativity-oriented research practices in HCI.
David Ribes' work explores the definition of domain in computing and data science; offers insight into how studying domains helps organize computational systems.
What I think Smalltalk should look like in 2018 is something like JuPyter / iPython notebook. Or, at a pinch, HyperCard.I open "Smalltalk" (whether that's a browser-based version equivalent to Amber, LivelyKernel or Peter Fisk's Smalltalk Express, or a desktop version like PharoLanguage or SqueakLanguage), and what I see is a "smart notebook" type metaphor :A single page that takes up the whole window. To which I can start adding "cells" or "cards" containing either code or "literate" style documentation, or output produced by the code.You'd still have tools like the Class Browser etc. But they'd be integrated within the same UI. Ie. the class browser is just more "pages" in the notebook. There's no workspace or transcript because every page can have live code on it.This UI is immediate. And focused on "do something".
On a similar approach, I created and actively developed from 2014 to 2019 Grafoscopio, which, while being inside Pharo and a companion of all other tools, was providing a computable outliner to do something: write computable and reproducible documents and bridge the gap between the IDE and the app for a more mature audience (a similar approach for children was previously tested in Squeak, with Etoys).
This allowed me to write the Grafoscopio Manual (2016) inside Grafoscopio or to do with the community some hacktivist republishing, like we did with the Data Journalism Handbook (2018)
Of course, being those initiatives from the so called "Global South" and being Grafoscopio my first "real program" ever, they lacked the visibility of Global North initiatives, like the ones you collected in Smart Academic Notebook, but they were acknowledge and appreciated in small/specialized communities, like the Pharo community.
With the new GUI/DX provided by Lepiter (2021), I have been migrating the Grafoscopio Lessons from the previous half decade to this technology, with the MiniDocs package and I imagine Grafoscopio becoming more a software distribution on top of Pharo/GT, providing documentation and collaboration workflows and improved outlining with packages like TiddlyWikiPharo or the Brea decoupled CMS / static site generator.
BTW, as I don't know how to add comments or suggest updates I wonder why this note is not updated with Lepiter as it provides pretty much the experience you were advocating for since 2018 and it is already in your wiki/bliki. Maybe it is just a matter of some wiki refactoring a links update.
The Computational Democracy Project
We bring data science to deliberative democracy, so that governance may better reflect the multidimensionality of the public's will.
when provided with identical source code, input data, software, and computing environment configurations, that an independent party can exactly reproduce the results of the original work -- especially published results. Thi
The reproduction of the original source giving as a result the same source code, input data, software and configurations in the system might be considered as Computational reproducibility
resource-scarce language
This app seems to focus on Grade 3 isiZulu and then english.
computational boundary of the self notion is simply a way to try to be able to think about very diverse kinds of uh beings diverse kinds 00:08:12 of intelligences all all on one scale
for: purpose - computational boundary of self - it's utility is to have one idea that can help define intelligence non-anthropomorphically, not just of humans
it's easy for us to look at us and think okay we're 30 trillion human cells give or take we're about 39 trillion bacterial cells at what point do we consider ourselves bacteria or at what point do we consider ourselves 00:07:46 human
for - question - identity - individual cell vs multicellular organism
question - identity - individual cell vs multicellular organism - This is a fascinating question as it looks at our evolutionarily composite nature - as a multi-scale competency architecture - Certainly our ordinary consciousness operates as the governance system for the entire population of collaborating cells and microbes - but can we actually directly identify with each individual cell or microbe in this vast integrated collection? - how does Levin's computational boundary of self help to shed light on this question?
there are certain areas within CSS that are reluctant to adopt rigorous scientific practices from other fields, which can be observed through an overreliance on passively collected data (e.g., through digital traces, wearables) without questioning the validity of such data.
as Computational Social Science (CSS) grows up, it must strike a balance between its own practices and those of neighboring disciplines to achieve scientific rigor and refine its identity.
computational social science as an interdisciplinary scientific field in which contributions develop and test theories or provide systematic descriptions of human, organizational, and institutional behavior through the use of computational methods and practices.
Given that the array of tokens grows with the amount of code we have in a file, that doesn't sound ideal. There are more efficient algorithms to search a value in an array that we can use rather than going through every element in the array. Replacing that line with a binary search for example cuts the time in half.
an overview of the paper
paper overview
Levin was interested in any conceivable type of cognitive system and was interested in find a way to universally characterize them all
Levin had been thinking about this for years
the computational boundary of a self
for: self, self - computational boundary, Michael Levin
title: The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition
Zhao, W. J., Coady, A., & Bhatia, S. (2021). Computational mechanisms for context-based behavioral interventions: A large-scale analysis. PsyArXiv. https://doi.org/10.31234/osf.io/8cyad
Atari, M., Reimer, N. K., Graham, J., Hoover, J., Kennedy, B., Davani, A. M., Karimi-Malekabadi, F., Birjandi, S., & Dehghani, M. (2021). Pathogens Are Linked to Human Moral Systems Across Time and Space. PsyArXiv. https://doi.org/10.31234/osf.io/tnyh9
This course is an introduction to computational theories of human cognition. Drawing on formal models from classic and contemporary artificial intelligence, we will explore fundamental issues in human knowledge representation, inductive learning and reasoning. What are the forms that our knowledge of the world takes?
When?
Furl, N., McKay, R., & Coltheart, M. (2022, January 29). The Paradox of Delusions: Are Deluded Individuals Resistant to Evidence?. https://doi.org/10.31234/osf.io/e37c2
Krueger, P., Callaway, F., Gul, S., Griffiths, T., & Lieder, F. (2022). Discovering Rational Heuristics for Risky Choice. PsyArXiv. https://doi.org/10.31234/osf.io/mg7dn
Grimmer & Stewart (2013) - Text as Data: The Promise and Pitfalls of Automatic ContentAnalysis Methods for Political Texts
Nelson (2020) - Computational Grounded Theory: A Methodological Framework
Palminteri, S. (2021). Choice-confirmation bias and gradual perseveration in human reinforcement learning [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/dpqj6
Singh, Urvashi B., Mercy Rophina, Dr Rama Chaudhry, Vigneshwar Senthivel, Kiran Bala, Rahul C. Bhoyar, Bani Jolly, et al. “Variants of Concern Responsible for SARS-CoV-2 Vaccine Breakthrough Infections from India.” OSF Preprints, June 3, 2021. https://doi.org/10.31219/osf.io/fgd4x.
has been adapted to thecomputational model in [14]; it uses type annotations to help the proo
Burton, J. W., Cruz, N., & Hahn, U. (2021). Reconsidering evidence of moral contagion in online social networks. Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01133-5
Quillien, Tadeg, and Michael Barlev. ‘Causal Judgment in the Wild: Evidence from the 2020 US Presidential Election’. PsyArXiv, 7 April 2021. https://doi.org/10.31234/osf.io/7w9re.
Knowles, R., Mateen, B. A., & Yehudi, Y. (2021). We need to talk about the lack of investment in digital research infrastructure. Nature Computational Science, 1(3), 169–171. https://doi.org/10.1038/s43588-021-00048-5
Holme, Petter, and Jari Saramäki. ‘Temporal Networks as a Modeling Framework’. ArXiv:2103.13586 [Physics], 24 March 2021. http://arxiv.org/abs/2103.13586.
Nsoesie, E. O., Oladeji, O., Abah, A. S. A., & Ndeffo-Mbah, M. L. (2021). Forecasting influenza-like illness trends in Cameroon using Google Search Data. Scientific Reports, 11(1), 6713. https://doi.org/10.1038/s41598-021-85987-9
Hong, B., Bonczak, B. J., Gupta, A., Thorpe, L. E., & Kontokosta, C. E. (2021). Exposure density and neighborhood disparities in COVID-19 infection risk. Proceedings of the National Academy of Sciences, 118(13). https://doi.org/10.1073/pnas.2021258118
Indiana University Network Science Institute. ‘Alessandro Vespignani on Computational Epidemiology at the Time of COVID-19’. Accessed 7 March 2021. http://iuni.iu.edu/news/event/59.
ReconfigBehSci. (2020, November 23). RT @lakens: Ongoing, an incredibly awesome talk on computational reproducibility by @AdinaKrik. Slides: Https://t.co/QslHW3gEtm. If you are… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1331265422109396995
2020 Conference on Computational Sociology | IRiSS. (n.d.). Retrieved 30 September 2020, from https://iriss.stanford.edu/css/conferences/2020-conference-computational-sociology
Fareri, Dominic S., Joanne Stasiak, and Peter Sokol-Hessner. ‘Choosing for Another: Social Context Changes Dissociable Computational Mechanisms of Risky Decision-Making’, 21 September 2020. https://doi.org/10.31234/osf.io/dr42a.
Holme, P. (2020). Fast and principled simulations of the SIR model on temporal networks. ArXiv:2007.14386 [Physics, q-Bio]. http://arxiv.org/abs/2007.14386
Spreckelsen, P. von, Wessel, I., Glashouwer, K., & Jong, P. J. de. (2020). Preprint Averting Repulsion? Body-Directed Self-Disgust and Autobiographical Memory Retrieval. https://doi.org/10.31234/osf.io/qhc35
Ben-David, S. (2018). Clustering—What Both Theoreticians and Practitioners are Doing Wrong. ArXiv:1805.08838 [Cs, Stat]. http://arxiv.org/abs/1805.08838
Sharma, N., Uttrani, S., & Dutt, V. (2020, June 19). Modeling the Absence of Framing Effect in an Experience-based Covid-19 Disease Problem. 18th Annual Meeting of the International Conference on Cognitive Modelling. https://www.researchgate.net/publication/342313460_Modeling_the_Absence_of_Framing_Effect_in_an_Experience-based_Covid-19_Disease_Problem
Hopp, F. R., Fisher, J. T., Cornell, D., Huskey, R., & Weber, R. (2020). The Extended Moral Foundations Dictionary (eMFD): Development and Applications of a Crowd-Sourced Approach to Extracting Moral Intuitions from Text [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/924gq
Hertz, U. (2020). Cognitive learning processes account for asymmetries in adaptations to new social norms [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/7thku
Stevens, H. & Muyskens, J. (2020 May 14). See how experts use disease modeling to predict coronavirus cases after states reopen. Washington Post. https://www.washingtonpost.com/graphics/2020/health/disease-modeling-coronavirus-cases-reopening/
Edelmann, A., Wolff, T., Montagne, D., & Bail, C. A. (2020). Computational Social Science and Sociology. Annual Review of Sociology, 46(1), annurev-soc-121919-054621. https://doi.org/10.1146/annurev-soc-121919-054621
Vespignani, A., Tian, H., Dye, C. et al. Modelling COVID-19. Nat Rev Phys (2020). https://doi.org/10.1038/s42254-020-0178-4
Lengersdorff, L., Wagner, I., & Lamm, C. (2020, April 20). When implicit prosociality trumps selfishness: the neural valuation system underpins more optimal choices when learning to avoid harm to others than to oneself. https://doi.org/10.31234/osf.io/q6psx
\Uk7!U"shouldbe\U7!Uk"
The inverse is true. The text contains "U -> U^k".
Recent reviews on DFT may be found in Jones and Gunnarsson (1989) and Dreizler andGross (1990)
This is before the PAW method came along (Blochl '94), so probably nothing method-specific.
In contrast, activities of invention almost always progress towards the creation of new or better things but not necessarily through refi nement. Normally we invent by combining a set of things we already understand how to create into larger, more complex, or more capable things that did not previously exist.
The purpose of HCI as invention:
• "understanding can sometimes decrease" due to complexity of making things
• "things are more capable"
Activities of discovery can have a variety of aims, including generating rich, empirically based descriptions, and creating new theoretical understandings
The purpose of HCI as discovery:
•"form framing truths"
• elaborate to "progress toward improved understandings"
• refined to "explain more phenomena or to be more predictive"
• "developing and testing competing ideas"
Another way of understanding technical HCI research is by contrasting it with other types of technical work that is not research. For our purposes, research can be seen as having the creation of reusable knowledge at its core. More specifi cally technical HCI research emphasizes knowledge about how to create something (invention) but also knowledge that might be reused to assist in the creation of a whole class of similar things or even multiple types of different things.
HCI research definition. Contrast this with the previous development-based definition.
In an interdisciplinary setting such as HCI, we often shift between disciplines that have stable and functional but potentially con-tradictory world views. In doing so, we are confronted with the need to select and use (or at least appreciate, understand, and evaluate) a wide range of methods and with them a wide range of expectations and values.
The interdiscipliinary nature of HCI provides an impetus to consider non-STEM perspectives but can also reveal frictions between approaches, practices, values, and goals.
Technical HCI focuses on the technology and improvement aspects of this task—it seeks to use technology to solve human problems and improve the world. To accom-plish this, the fundamental activity of technical HCI is one of invention —we seek to use technology to expand what can be done or to fi nd how best to do things that can already be done.
HCI definition
How strange! She looked up at the pale sky, and all she thought was, “Yes, it was the most successful party.”
There is no denying that Laura thinks a party with the dead is not a successful party. So I supposed that it is a verbal irony. There are also many ironies in The Moonstone. How can we track the irony through a computational method? I think this example of irony gives me an inspiration. There are some passive words which indicate the meaning that is ostensibly expressed in this paragraph, but "the most successful" are positive words. The strong contrast can be a typical symbol for the computer to recognize irony.
浙大计算摄像学课程
A Global Database of Society
interesting
Do you have questions about how best to moderate your online community? CivilServant, software created at the MIT Center for Civic Media, helps online communities do your own A/B tests of moderation practices.
This is an interesting SaaS system for exploring how to create good moderation systems.
I always found it incredible. He would start with some problem, and fill up pages with calculations. And at the end of it, he would actually get the right answer! But he usually wasn’t satisfied with that. Once he’d gotten the answer, he’d go back and try to figure out why it was obvious. And often he’d come up with one of those classic Feynman straightforward-sounding explanations. And he’d never tell people about all the calculations behind it. Sometimes it was kind of a game for him: having people be flabbergasted by his seemingly instant physical intuition, not knowing that really it was based on some long, hard calculation he’d done.
Straightforward intuition isn't just intuition.
It reminds me of the New Math of the 1960s, which fashioned mathematics in a dramatically more abstract, more analytic way than before. And if Johnny Can’t Add with the new math, maybe Jenny Won’t Code with an overly abstract presentation of computing. Papert points us in the opposite direction
It’s a source of power to do something and figure things out, in a dance between the computer and our thoughts. The inversion, starting with computing as a formal thing to understand and then come to the application later, takes away its power.
One striking comment follows a couple of pages later, where the phrase “computer-aided instruction” evokes in Papert the unappealing idea that “the computer is being used to program the child” — his vision, of course, is that the child must program the computer.
In 1980, Seymour Papert published the book “Mindstorms: Children, Computers, and Powerful Ideas” [2]. Papert was co-director, under Marvin Minsky, of the MIT Artificial Intelligence Laboratory from 1967 to 1981. Previously, he had worked with Jean Piaget in Geneva. Piaget was a developmental psychologist best known for pioneering the learning theory known as constructivism: simply put, that learners construct new knowledge (in their minds) from the interaction of their experiences with previous knowledge. Papert, in turn, developed the theory of constructionism, adding the notion that learning is enhanced when the learner is engaged in “constructing a meaningful product.”