- Oct 2024
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fathom.video fathom.video
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what is the nature of the invitation.
for - group dynamics of expanding and converging groups
group dynamics of expanding and converging groups - It is natural for groups to expand and grow and when they do, it changes the dynamics of the social interactions - Effort is required to know each other. It requires time to share and absorb what is shared - That legacy knowledge becomes the unspoken and implicit ground for future discourse - When new people are introduced to a group, or new groups are introduced to each other, - a minimum amount of sharing is required to establish common ground, common understanding - When members of a group have unique ideas to share, - a standardized, shareable documentation may become necessary for greater efficacy of sharing - the constitutions that are often at the heart of institutions became necessary for the same reasons
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www.liberatingstructures.com www.liberatingstructures.com
- Aug 2024
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arxiv.org arxiv.org
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for - Indyweb dev - large language model for - constructing causal loop diagrams - System Dynamics Bot - large language model - constructing causal loop diagrams
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- Jul 2024
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www.holacracy.org www.holacracy.org
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I don’t want to just have a voice — I want my voice to have value and impact.
From green to Yellow SD
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Annotators
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- Jun 2024
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coevolving.com coevolving.com
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The system behaviour emerges only in the dynamics of the interactions of the parts. This is not a cumulative linear effect but rather a cyclical causal effect
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- Apr 2024
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cwodtke.medium.com cwodtke.medium.com
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MDA, a theory of how game design works. MDA is a theory about the emergent nature of game play. It says when you combine game MECHANICS (shoot something, collect coins, jump over something, open a locked door, etc) the combination becomes DYNAMICS (sidescroller, boss battle, etc) which then is experienced by a player as a type of fun, or AESTHETICS (Fellowship, Challenge, Fantasy etc.
Mechanics, dynamics and aesthetics
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- Jan 2024
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www.derstandard.at www.derstandard.at
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Aktueller Überblick zu Emissionen und Landnutzung in Österreich die Emissionen durch die Landwirtschaft nehmen schon länger ab, während Wälder in Österreich zunehmend als CO2 senken fungieren. Wichtigste Ursache für die Emissionen ist nach wie vor die Viehhaltung. Https://www.derstandard.at/story/3000000200378/wie-die-landnutzung-helfen-kann-das-klima-zu-schuetzen
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- Dec 2023
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Glossary of some important musical terms
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- mode-hemiolic
- monophony
- double-note
- mesotony
- source:nikolsky-glossary
- modes-heptatonic
- heterophony
- modes-monotonic
- monody
- multitony
- pitch-class
- mode-timbral
- interval-class
- phrase
- rhythm
- tonality
- melodic-inclination
- form
- phrase-climax
- modes-diatonic
- tone-class
- consonance-melodic
- phrase-cadence
- modes-tritonic
- meter
- articulation
- melody
- texture-polyphony
- instrumentation
- phrasing
- texture
- tonicity
- tonal-gravity
- harmony
- texture-voluminousness
- diatonic-modes
- mode-ekmelic
- texture-part-vs-voice
- modality
- dissonance
- tempo
- modes-octatonic
- motif
- dissonance-melodic
- rhythm-class
- modes-hexatonic
- dissonance-harmonic
- register
- mode-rhythmic
- consonance
- modes-tetratonic
- hypermode
- modal-harmony
- AOEs
- modes
- diatony
- mode-khasmatonal
- dynamics
- melodic-intonation
- modes-pentatonic
Annotators
URL
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- Sep 2023
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www.youtube.com www.youtube.com
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08:00 his sword technique was adaptable, mendable, consistent with the complex nature of reality, that changes constantly, not resisting change but adapting self to it
- see zk on how a more dynamic approach to productivity and systems can help us reflect reality more closely, ever changing
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en.wikipedia.org en.wikipedia.org
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Spiral Dynamics (SD) is a model of the evolutionary development of individuals, organizations, and societies. It was initially developed by Don Edward Beck and Christopher Cowan based on the emergent cyclical theory of Clare W. Graves, combined with memetics as proposed by Richard Dawkins and further developed by Mihaly Csikszentmihalyi.
https://en.wikipedia.org/wiki/Spiral_Dynamics
related to ideas I've had with respect to Werner R. Loewenstein?
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- Jun 2023
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comedycenter.org comedycenter.org
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Melissa Rivers also announced today the launch of a special edition 4-disc CD box set collection titled “Joan Rivers – The Diva Rides Again” that will feature five hours of never-before-released recordings of Joan’s comedy, including six decades worth of hilarious material and a special 16-page collector’s book of liner notes with never-before-seen photos. The box set is currently available for preorder on Amazon, Target.com and Walmart.com and will be released on August 18, 2023 on streaming platforms such as iTunes and Spotify. The set is produced and distributed by Comedy Dynamics in partnership with the Joan Rivers estate.
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www.youtube.com www.youtube.com
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22:30 Differing environments/context matters. So before giving tricks, hacks, etc. realise that you function within a different environment.
Historicity is a historical sibling to this: periods have different environments, and thus don't apply 1 on 1.
But we can still learn from other other people & periods?
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docdrop.org docdrop.org
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AsSchullerpointsout:“Thereisnoquestioninmymindthat theclassicalworldcanlearnmuchabout timing.rhythmicaccuracyand subtlety fromjazzmusicians,asjazzmusicianscanindynamics.structureandcontrastfromthe classical musicians.”
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docdrop.org docdrop.orgJazz1
- May 2023
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www.mendeley.com www.mendeley.com
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www.mendeley.com www.mendeley.com
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As Schuller points out: “There is no question in my mind that the classical world can learn much about timing. rhythmic accuracy and subtlety from jazz musicians, as jazz musicians can in dynamics. structure and contrast from the classical musicians.”
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www.mendeley.com www.mendeley.com
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dynam
dynamics as improvisation aid - accenting every 2nd note, for example
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www.mendeley.com www.mendeley.com
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Dynamics are yet another aspect of composition over which McNeely exercises deliberate and organized control. Writing for a high level ensemble such as the Vanguard Jazz Orchestra, he is able to demand and receive a great deal of nuance, shape and color. McNeely uses an extraordinarily high number of dynamic markings throughout all his arrangements and in particular here. Undulating hairpin (crescendo followed by immediate decrescendo) shapes are prevalent with each dynamic level marked 14specifically. As a rule, the ensemble exaggerates the dynamic shapes, often in ways that give prominence to the dynamics over and above elements of harmony and melody. In this respect, the dynamics may sometimes be considered a compositional device of equal importance. This general approach to dynamics as shapes is characteristic of all three of the compositions studied herein.
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- Apr 2023
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beiner.substack.com beiner.substack.com
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Daniel Schmachtenberger has spoken at length about the ‘generator functions’ of existential risk, in essence the deeper driving causes.
Definition - generator function of existential risk - the deeper driving cause of existential risk - two examples of deep causes - rivalrous dynamics - complicated systems consuming their complex substrate
Claim - Alexander Beiner claims that - the generator function of these generator functions is physicalism
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- Mar 2023
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insightmaker.com insightmaker.com
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// Insight Maker is used to model system dynamics and create agent based models by creating causal loop diagrams and allowing users to run simulations on those
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- Feb 2023
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docdrop.org docdrop.org
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Kawakatsu et al. (1) make an important ad-vance in the quest for this kind of understanding, pro-viding a general model for how subtle differences inindividual-level decision-making can lead to hard-to-miss consequences for society as a whole.Their work (1) reveals two distinct regimes—oneegalitarian, one hierarchical—that emerge fromshifts in individual-level judgment. These lead to sta-tistical methods that researchers can use to reverseengineer observed hierarchies, and understand howsignaling systems work when prestige and power arein play.
M. Kawakatsu, P. S. Chodrow, N. Eikmeier, D. B. Larremore, Emergence of hierarchy in networked endorsement dynamics. Proc. Natl. Acad. Sci. U.S.A. 118, e2015188118 (2021)
This may be of interest to Jerry Michalski et al.
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- Jan 2023
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Local file Local file
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one reason the Golden Age of Piracy remains the stuff oflegend is that pirates of that age were so skilled at manipulatinglegends; they deployed wonder-stories—whether of terrifyingviolence or inspiring ideals—as something very much like weaponsof war, even if the war in question was the desperate and ultimatelydoomed struggle of a motley band of outlaws against the entireemerging structure of world authority at the time.
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- Nov 2022
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blog.mahabali.me blog.mahabali.me
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https://blog.mahabali.me/pedagogy/pedagogical-snacking-transforming-classroom-dynamics/
Providing a snack break during classes can dramatically improve the participants' participation and cohesion.
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- Oct 2022
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read.aupress.ca read.aupress.ca
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Mead (1934) suggests that an individual’s identity is created by the degree to which that person absorbs the values of their community, summarized in the phrase “self reflects society.” Snow (2001) also argues that identity is largely constructed socially and includes, as well as Mead’s sense of belonging, a sense of difference from other communities. Identity is seen as a shared sense of “we-ness” developed through shared attributes and experiences and in contrast to one or more sets of others.
Consider in reference to the faculty/staff divide, to arguments over Faculty Status, to contingency, etc.
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- Sep 2022
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Results indicate that between the ages of 20 and75 years, nearly 60 percent of Americans will experience living for at least 1 yearbelow the official poverty line, while three-fourths of Americans will encounterpoverty or near- poverty (150 percent below the official poverty line).4
Mark Rank and Thomas Hirschl's research based on the Panel Study of Income Dynamics (PSID) using risk assessments using life tables show that nearly 60 percent of Americans between 20 and 75 will live for at least 1 year below the poverty line and 75% of Americans will encounter poverty or near-poverty (defined as 150 percent below the official poverty line).
Cross reference:<br /> Mark R. Rank and Thomas A. Hirschl, “The Likelihood of Experiencing Relative Poverty Across the Life Course,” PLoS One 10 (2015): E01333513.
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- Mar 2022
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psyarxiv.com psyarxiv.com
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Villanueva, Cynthia, Stevi Ibonie, Emily Jensen, Lucca Eloy, Jordi Quoidbach, Angela Bryan, Sidney D’Mello, and June Gruber. ‘Emotion Differentiation and Bipolar Risk in Emerging Adults Before and During the COVID-19 Pandemic’. PsyArXiv, 19 February 2022. https://doi.org/10.31234/osf.io/xya43.
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- Feb 2022
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Local file Local file
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Dweck shows convincingly thatthe most reliable predictor for long-term success is having a “growthmindset.” To actively seek and welcome feedback, be it positive ornegative, is one of the most important factors for success (andhappiness) in the long run. Conversely, nothing is a bigger hindranceto personal growth than having a “fixed mindset.” Those who fearand avoid feedback because it might damage their cherishedpositive self-image might feel better in the short term, but will quicklyfall behind in actual performance (Dweck 2006; 2013).
Carol Dweck shows that the most reliable predictor for long-term success is what she calls having a "growth mindset" or the ability to take feedback and change.
This seems related to the idea of endergonic reactions and the growth of complexity as well as the idea of the meaning of life.
What do these systems all have in common? What are their differences? What abstractions can we make from them?
Relate this to https://hypothes.is/a/pdWppIX5EeyhR0NR19OjCQ
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- Jan 2022
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academic.oup.com academic.oup.com
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Yonker, L. M., Boucau, J., Regan, J., Choudhary, M. C., Burns, M. D., Young, N., Farkas, E. J., Davis, J. P., Moschovis, P. P., Bernard Kinane, T., Fasano, A., Neilan, A. M., Li, J. Z., & Barczak, A. K. (2021). Virologic Features of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children. The Journal of Infectious Diseases, 224(11), 1821–1829. https://doi.org/10.1093/infdis/jiab509
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- Nov 2021
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www.theatlantic.com www.theatlantic.com
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It’s not just the hyper-social and the flirtatious who have found themselves victims of the New Puritanism. People who are, for lack of a more precise word, difficult have trouble too. They are haughty, impatient, confrontational, or insufficiently interested in people whom they perceive to be less talented. Others are high achievers, who in turn set high standards for their colleagues or students. When those high standards are not met, these people say so, and that doesn’t go over well. Some of them like to push boundaries, especially intellectual boundaries, or to question orthodoxies. When people disagree with them, they argue back with relish.
How much of this can be written down to differing personal contexts and lack of respect for people's humanity? Are the neurodivergent being punished in these spaces?
Applebaum provides a list of potential conflict areas of cancel culture outside of power dynamics.
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Once it was not just okay but admirable that Chua and Rubenfeld had law-school students over to their house for gatherings. That moment has passed. So, too, has the time when a student could discuss her personal problems with her professor, or when an employee could gossip with his employer. Conversations between people who have different statuses—employer-employee, professor-student—can now focus only on professional matters, or strictly neutral topics. Anything sexual, even in an academic context—for example, a conversation about the laws of rape—is now risky.
Is it simply the stratification of power and roles that is causing these problems? Is it that some of this has changed and that communication between people of different power levels is the difficulty in these cases?
I have noticed a movement in pedagogy spaces that puts the teacher as a participant rather than as a leader thus erasing the power structures that previously existed. This exists within Cathy Davidson's The New Education where teachers indicate that they're learning as much as their students.
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- Oct 2021
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www.jstor.org www.jstor.org
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Team syntegrity and democratic group decision making: theory and practice
Team Syntegrity
Stafford Beer created Team Syntegrity as a methodology for social interaction that predisposes participants towards shared agreement among varied and sometimes conflicting interests, without compromising the legitimate claims and integrity of those interests. This paper outlines the methodology and the underlying philosophy, describing several applications in a variety of countries and contexts, indicating why such an approach causes us to re-think more traditional approaches to group decision processes, and relating Team Syntegrity to other systems approaches.
Shared by Kirby Urner in the Trimtab Book Club
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- Jun 2021
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arxiv.org arxiv.org
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Reis, E. F. dos, & Masuda, N. (2021). Metapopulation models imply non-Poissonian statistics of interevent times. ArXiv:2106.10348 [Physics]. http://arxiv.org/abs/2106.10348
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- Apr 2021
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psyarxiv.com psyarxiv.com
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Betsch, Cornelia, and Philipp Sprengholz. ‘The Human Factor between Airborne Pollen Concentrations and COVID-19 Disease Dynamics’. PsyArXiv, 16 April 2021. https://doi.org/10.31234/osf.io/hw9gf.
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- Mar 2021
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www.scientificamerican.com www.scientificamerican.com
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Oreskes, N. (n.d.). Jeffrey Epstein’s Harvard Connections Show How Money Can Distort Research. Scientific American. https://doi.org/10.1038/scientificamerican0920-84
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- Feb 2021
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psyarxiv.com psyarxiv.com
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Jacobson, N. C., Price, G., Song, M., Wortzman, Z., Nguyen, N. D., & Klein, R. J. (2020, October 27). Machine Learning Models Predicting Daily Affective Dynamics Via Personality and Psychopathology Traits. https://doi.org/10.31234/osf.io/2zgv6
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- Jan 2021
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psyarxiv.com psyarxiv.com
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Dideriksen, C., Christiansen, M. H., Tylén, K., Dingemanse, M., & Fusaroli, R. (2020, October 12). Building common ground: Quantifying the interplay of mechanisms that promote understanding in conversations. https://doi.org/10.31234/osf.io/a5r74
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Landry. N., Restrepo. J. G. (2020).The effect of heterogeneity on hypergraph contagion models. Physics and Society. Retrieved from: https://arxiv.org/abs/2006.15453
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- Nov 2020
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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by attaching acceptor and donor to different domains of a target protein, the interdomain dynamics can be monitored
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www.michellekimconsulting.com www.michellekimconsulting.com
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What’s truly sad (but not shocking) about this whole situation is that this person, James Damore, a Havard educated, seemingly well-intentioned fella, had steadfast beliefs based on his complete misunderstanding of how “sexism” or “discrimination” actually work.And that’s the problem with the way we talk about diversity and inclusion in the business world.People are learning about unconscious bias WITHOUT the foundational knowledge of the cycle of socialization.People are learning about microaggressions WITHOUT the context of power dynamics.People are learning about “diversity programs” WITHOUT true understanding of concepts such as privilege or allyship.
While there are some people with good intents in the [[DEI]] space - it's starting to become apparent that there are some [[foundational concepts]] that we are missing, such as understanding how [[cycle of socialization]] impacts [[unconscious bias]]
or not understanding the role of [[power dynamics]] and [[microaggression]]
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- Oct 2020
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Maia, H. P., Ferreira, S. C., & Martins, M. L. (2020). Adaptive network approach for emergence of societal bubbles. ArXiv:2010.08635 [Nlin, Physics:Physics]. http://arxiv.org/abs/2010.08635
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covid-19.iza.org covid-19.iza.org
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COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved October 10, 2020, from https://covid-19.iza.org/publications/dp13569/
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Ghavasieh, A., Nicolini, C., & De Domenico, M. (2020). Statistical physics of complex information dynamics. ArXiv:2010.04014 [Cond-Mat, Physics:Physics]. http://arxiv.org/abs/2010.04014
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link.aps.org link.aps.org
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Gaisbauer, F., Olbrich, E., & Banisch, S. (2020). Dynamics of opinion expression. Physical Review E, 102(4), 042303. https://doi.org/10.1103/PhysRevE.102.042303
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link.aps.org link.aps.org
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Burda, Z., Kotwica, M., & Malarz, K. (2020). Ageing of complex networks. Physical Review E, 102(4), 042302. https://doi.org/10.1103/PhysRevE.102.042302
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www.pnas.org www.pnas.org
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Karatayev, Vadim A., Madhur Anand, and Chris T. Bauch. ‘Local Lockdowns Outperform Global Lockdown on the Far Side of the COVID-19 Epidemic Curve’. Proceedings of the National Academy of Sciences 117, no. 39 (29 September 2020): 24575–80. https://doi.org/10.1073/pnas.2014385117.
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- Sep 2020
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Chen, Q., & Porter, M. A. (2020). Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks. ArXiv:2009.12932 [Physics]. http://arxiv.org/abs/2009.12932
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arxiv.org arxiv.org
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James, N., & Menzies, M. (2020). Human and financial cost of COVID-19. ArXiv:2009.11660 [Physics, q-Fin]. http://arxiv.org/abs/2009.11660
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twitter.com twitter.com
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Pausal Živference on Twitter. (n.d.). Twitter. Retrieved September 26, 2020, from https://twitter.com/PausalZ/status/1309208611265093632
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science.sciencemag.org science.sciencemag.org
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Saad-Roy, C. M., Wagner, C. E., Baker, R. E., Morris, S. E., Farrar, J., Graham, A. L., Levin, S. A., Mina, M. J., Metcalf, C. J. E., & Grenfell, B. T. (2020). Immune life history, vaccination, and the dynamics of SARS-CoV-2 over the next 5 years. Science. https://doi.org/10.1126/science.abd7343
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www.imperial.ac.uk www.imperial.ac.uk
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COVID-19 reports. (n.d.). Imperial College London. Retrieved September 17, 2020, from http://www.imperial.ac.uk/medicine/departments/school-public-health/infectious-disease-epidemiology/mrc-global-infectious-disease-analysis/covid-19/covid-19-reports/
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Giles, J. R., Erbach-Schoenberg, E. zu, Tatem, A. J., Gardner, L., Bjørnstad, O. N., Metcalf, C. J. E., & Wesolowski, A. (2020). The duration of travel impacts the spatial dynamics of infectious diseases. Proceedings of the National Academy of Sciences, 117(36), 22572–22579. https://doi.org/10.1073/pnas.1922663117
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academic.oup.com academic.oup.com
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Kahn, R., Kennedy-Shaffer, L., Grad, Y. H., Robins, J. M., & Lipsitch, M. (n.d.). Potential Biases Arising from Epidemic Dynamics in Observational Seroprotection Studies. American Journal of Epidemiology. https://doi.org/10.1093/aje/kwaa188
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github.com github.com
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aaronpeikert. (2020). Aaronpeikert/reproducible-research [TeX]. https://github.com/aaronpeikert/reproducible-research (Original work published 2019)
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Miyoshi, S., Jusup, M., & Holme, P. (2020). Flexible imitation mechanisms suppress epidemics through better vaccination. ArXiv:2009.00443 [Physics, q-Bio]. http://arxiv.org/abs/2009.00443
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arxiv.org arxiv.org
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Carmona, H. A., de Noronha, A. W. T., Moreira, A. A., Araujo, N. A. M., & Andrade Jr, J. S. (2020). Cracking urban mobility. ArXiv:2008.13644 [Cond-Mat, Physics:Physics]. http://arxiv.org/abs/2008.13644
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- Aug 2020
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link.aps.org link.aps.org
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Perez, I. A., Di Muro, M. A., La Rocca, C. E., & Braunstein, L. A. (2020). Disease spreading with social distancing: A prevention strategy in disordered multiplex networks. Physical Review E, 102(2), 022310. https://doi.org/10.1103/PhysRevE.102.022310
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Waites, W., Cavaliere, M., Manheim, D., Panovska-Griffiths, J., & Danos, V. (2020). Scaling up epidemiological models with rule-based modelling. ArXiv:2006.12077 [q-Bio]. http://arxiv.org/abs/2006.12077
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covid-19.iza.org covid-19.iza.org
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Dynamics of Social Mobility during the COVID-19 Pandemic in Canada. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved August 4, 2020, from https://covid-19.iza.org/publications/dp13376/
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Moya, C., Cruz y Celis Peniche, P. D., Kline, M. A., & Smaldino, P. (2020). Dynamics of Behavior Change in the COVID World [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/kxajh
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www.medrxiv.org www.medrxiv.org
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Starnini, M., Aleta, A., Tizzoni, M., & Moreno, Y. (2020). Impact of the accuracy of case-based surveillance data on the estimation of time-varying reproduction numbers. MedRxiv, 2020.06.26.20140871. https://doi.org/10.1101/2020.06.26.20140871
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Sun, F., Wang, X., Tan, S., Dan, Y., Lu, Y., Zhang, J., Xu, J., Tan, Z., Xiang, X., Zhou, Y., He, W., Wan, X., Zhang, W., Chen, Y., Tan, W., & Deng, G. (2020). SARS-CoV-2 Quasispecies provides insight into its genetic dynamics during infection. BioRxiv, 2020.08.20.258376. https://doi.org/10.1101/2020.08.20.258376
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Velásquez-Rojas, F., Ventura, P. C., Connaughton, C., Moreno, Y., Rodrigues, F. A., & Vazquez, F. (2020). Disease and information spreading at different speeds in multiplex networks. Physical Review E, 102(2), 022312. https://doi.org/10.1103/PhysRevE.102.022312
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Sun, K., Wang, W., Gao, L., Wang, Y., Luo, K., Ren, L., Zhan, Z., Chen, X., Zhao, S., Huang, Y., Sun, Q., Liu, Z., Litvinova, M., Vespignani, A., Ajelli, M., Viboud, C., & Yu, H. (2020). Transmission heterogeneities, kinetics, and controllability of SARS-CoV-2. MedRxiv, 2020.08.09.20171132. https://doi.org/10.1101/2020.08.09.20171132
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Cevik, M., Tate, M., Lloyd, O., Maraolo, A. E., Schafers, J., & Ho, A. (2020). SARS-CoV-2, SARS-CoV-1 and MERS-CoV viral load dynamics, duration of viral shedding and infectiousness: A living systematic review and meta-analysis. MedRxiv, 2020.07.25.20162107. https://doi.org/10.1101/2020.07.25.20162107
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arxiv.org arxiv.org
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Ran, Y., Deng, X., Wang, X., & Jia, T. (2020). A generalized linear threshold model for an improved description of the spreading dynamics. Chaos: An Interdisciplinary Journal of Nonlinear Science, 30(8), 083127. https://doi.org/10.1063/5.0011658
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Bisin, A., & Moro, A. (2020). Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses (Working Paper No. 27590; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27590
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www.nber.org www.nber.org
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Alon, T., Kim, M., Lagakos, D., & VanVuren, M. (2020). How Should Policy Responses to the COVID-19 Pandemic Differ in the Developing World? (Working Paper No. 27273; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27273
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Krueger, D., Uhlig, H., & Xie, T. (2020). Macroeconomic Dynamics and Reallocation in an Epidemic (Working Paper No. 27047; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27047
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Jinjarak, Y., Ahmed, R., Nair-Desai, S., Xin, W., & Aizenman, J. (2020). Accounting for Global COVID-19 Diffusion Patterns, January-April 2020 (Working Paper No. 27185; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27185
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Radicchi, F., & Bianconi, G. (2020). Epidemic plateau in critical SIR dynamics with non-trivial initial conditions. ArXiv:2007.15034 [Cond-Mat, Physics:Physics, q-Bio]. http://arxiv.org/abs/2007.15034
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- Jul 2020
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www.medrxiv.org www.medrxiv.org
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Golding, N., Russell, T. W., Abbott, S., Hellewell, J., Pearson, C. A. B., Zandvoort, K. van, Jarvis, C. I., Gibbs, H., Liu, Y., Eggo, R. M., Edmunds, J. W., & Kucharski, A. J. (2020). Reconstructing the global dynamics of under-ascertained COVID-19 cases and infections. MedRxiv, 2020.07.07.20148460. https://doi.org/10.1101/2020.07.07.20148460
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Reher, D. S., Requena, M., de Santis, G., Esteve, A., Bacci, M. L., Padyab, M., & Sandström, G. (2020). The COVID-19 pandemic in an aging world [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/bfvxt
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Rybniker, J., & Fätkenheuer, G. (2020). Importance of precise data on SARS-CoV-2 transmission dynamics control. The Lancet Infectious Diseases, S1473309920303595. https://doi.org/10.1016/S1473-3099(20)30359-5
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Liu, Y., Eggo, R. M., & Kucharski, A. J. (2020). Secondary attack rate and superspreading events for SARS-CoV-2. The Lancet, 395(10227), e47. https://doi.org/10.1016/S0140-6736(20)30462-1
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Cobey, S. (2020). Modeling infectious disease dynamics. Science, 368(6492), 713–714. https://doi.org/10.1126/science.abb5659
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Johnson, N.F., Velásquez, N., Restrepo, N.J. et al. The online competition between pro- and anti-vaccination views. Nature (2020). https://doi.org/10.1038/s41586-020-2281-1
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Masuda, N., & Holme, P. (2020). Small inter-event times govern epidemic spreading on networks. Physical Review Research, 2(2), 023163. https://doi.org/10.1103/PhysRevResearch.2.023163
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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
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arxiv.org arxiv.org
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Tuninetti, M., Aleta, A., Paolotti, D., Moreno, Y., & Starnini, M. (2020). Prediction of scientific collaborations through multiplex interaction networks. ArXiv:2005.04432 [Physics]. http://arxiv.org/abs/2005.04432
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sfi-edu.s3.amazonaws.com sfi-edu.s3.amazonaws.com
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The Santa Fe Institute - SFI Transmission PDF
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www.medrxiv.org www.medrxiv.org
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Buitrago-Garcia, D. C., Egli-Gany, D., Counotte, M. J., Hossmann, S., Imeri, H., Salanti, G., & Low, N. (2020). The role of asymptomatic SARS-CoV-2 infections: Rapid living systematic review and meta-analysis [Preprint]. Epidemiology. https://doi.org/10.1101/2020.04.25.20079103
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Arons, M. M., Hatfield, K. M., Reddy, S. C., Kimball, A., James, A., Jacobs, J. R., Taylor, J., Spicer, K., Bardossy, A. C., Oakley, L. P., Tanwar, S., Dyal, J. W., Harney, J., Chisty, Z., Bell, J. M., Methner, M., Paul, P., Carlson, C. M., McLaughlin, H. P., … Jernigan, J. A. (2020). Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility. New England Journal of Medicine, NEJMoa2008457. https://doi.org/10.1056/NEJMoa2008457
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Ghinai, I., Woods, S., Ritger, K. A., McPherson, T. D., Black, S. R., Sparrow, L., Fricchione, M. J., Kerins, J. L., Pacilli, M., Ruestow, P. S., Arwady, M. A., Beavers, S. F., Payne, D. C., Kirking, H. L., & Layden, J. E. (2020). Community Transmission of SARS-CoV-2 at Two Family Gatherings—Chicago, Illinois, February–March 2020. MMWR. Morbidity and Mortality Weekly Report, 69(15), 446–450. https://doi.org/10.15585/mmwr.mm6915e1
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Yong, S. E. F., Anderson, D. E., Wei, W. E., Pang, J., Chia, W. N., Tan, C. W., Teoh, Y. L., Rajendram, P., Toh, M. P. H. S., Poh, C., Koh, V. T. J., Lum, J., Suhaimi, N.-A. M., Chia, P. Y., Chen, M. I.-C., Vasoo, S., Ong, B., Leo, Y. S., Wang, L., & Lee, V. J. M. (2020). Connecting clusters of COVID-19: An epidemiological and serological investigation. The Lancet Infectious Diseases, S1473309920302735. https://doi.org/10.1016/S1473-3099(20)30273-5
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Zhu, Y., Bloxham, C. J., Hulme, K. D., Sinclair, J. E., Tong, Z. W. M., Steele, L. E., Noye, E. C., Lu, J., Chew, K. Y., Pickering, J., Gilks, C., Bowen, A. C., & Short, K. R. (2020). Children are unlikely to have been the primary source of household SARS-CoV-2 infections [Preprint]. Epidemiology. https://doi.org/10.1101/2020.03.26.20044826
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academic.oup.com academic.oup.com
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Danis, K., Epaulard, O., Bénet, T., Gaymard, A., Campoy, S., Bothelo-Nevers, E., Bouscambert-Duchamp, M., Spaccaferri, G., Ader, F., Mailles, A., Boudalaa, Z., Tolsma, V., Berra, J., Vaux, S., Forestier, E., Landelle, C., Fougere, E., Thabuis, A., Berthelot, P., … Bag, B. C. (2020). Cluster of coronavirus disease 2019 (Covid-19) in the French Alps, 2020. Clinical Infectious Diseases, ciaa424. https://doi.org/10.1093/cid/ciaa424
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Jing, Q.-L., Liu, M.-J., Yuan, J., Zhang, Z.-B., Zhang, A.-R., Dean, N. E., Luo, L., Ma, M.-M., Longini, I., Kenah, E., Lu, Y., Ma, Y., Jalali, N., Fang, L.-Q., Yang, Z.-C., & Yang, Y. (2020). Household Secondary Attack Rate of COVID-19 and Associated Determinants [Preprint]. Epidemiology. https://doi.org/10.1101/2020.04.11.20056010
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Bi, Q., Wu, Y., Mei, S., Ye, C., Zou, X., Zhang, Z., Liu, X., Wei, L., Truelove, S. A., Zhang, T., Gao, W., Cheng, C., Tang, X., Wu, X., Wu, Y., Sun, B., Huang, S., Sun, Y., Zhang, J., … Feng, T. (2020). Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: A retrospective cohort study. The Lancet Infectious Diseases, S1473309920302875. https://doi.org/10.1016/S1473-3099(20)30287-5
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Burke RM, Midgley CM, Dratch A, et al. Active Monitoring of Persons Exposed to Patients with Confirmed COVID-19 — United States, January–February 2020. MMWR Morb Mortal Wkly Rep 2020;69:245–246. DOI: http://dx.doi.org/10.15585/mmwr.mm6909e1
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pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov
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Yi, C., Aihong, W., Keqin, D., Haibo, W., Jianmei, W., Hongbo, S., Sijia,W., & Guozhang, X. (2020) The epidemiological characteristics of infection in close contacts of COVID-19 in Ningbo city. Chinese Journal of Epidemiology. Vol. 41 Issue (0):0-0. http://dx.doi.org/10.3760/cma.j.cn112338-20200304-00251
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twitter.com twitter.com
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Dr Muge Cevik on Twitter
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Contact tracing for COVID-19: Current evidence, options for scale-up and an assessment of resources needed. (2020, May 5). European Centre for Disease Prevention and Control. https://www.ecdc.europa.eu/en/publications-data/contact-tracing-covid-19-evidence-scale-up-assessment-resources
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psyarxiv.com psyarxiv.com
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Tomohiro, I. (2020, May 8). Consensus among group members’ shared leadership ratings polarizes group performance. https://doi.org/10.31234/osf.io/psjeu
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Local file Local file
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ecommended choice isgaff2
gaff2 is recommended for organic molecule
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www.nature.com www.nature.com
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Vespignani, A., Tian, H., Dye, C. et al. Modelling COVID-19. Nat Rev Phys (2020). https://doi.org/10.1038/s42254-020-0178-4
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Local file Local file
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ecommended choice isgaff2
gaff2 is recommended for organic compounds
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journals.plos.org journals.plos.org
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Rivkind, A., Schreier, H., Brenner, N., & Barak, O. (2020). Scale free topology as an effective feedback system. PLOS Computational Biology, 16(5), e1007825. https://doi.org/10.1371/journal.pcbi.1007825
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jamanetwork.com jamanetwork.com
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Steinbrook, R. (2020). Contact Tracing, Testing, and Control of COVID-19—Learning From Taiwan. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2020.2072
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Inglesby, T. V. (2020). Public Health Measures and the Reproduction Number of SARS-CoV-2. JAMA. https://doi.org/10.1001/jama.2020.7878
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Liu, L., Wang, X., Tang, S., & Zheng, Z. (2020). Complex social contagion induces bistability on multiplex networks. ArXiv:2005.00664 [Physics]. http://arxiv.org/abs/2005.00664
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www.economist.com www.economist.com
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Countries are using apps and data networks to keep tabs on the pandemic. (2020 March 26). The Economist. https://www.economist.com/briefing/2020/03/26/countries-are-using-apps-and-data-networks-to-keep-tabs-on-the-pandemic?fsrc=newsletter&utm_campaign=the-economist-today&utm_medium=newsletter&utm_source=salesforce-marketing-cloud&utm_term=2020-05-07&utm_content=article-link-1
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cbio.bmt.tue.nl cbio.bmt.tue.nl
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This is a good overview of the common potentials of a force field
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Martins, A. C. R. (2020). Extremism definitions in opinion dynamics models. ArXiv:2004.14548 [Nlin, Physics:Physics]. http://arxiv.org/abs/2004.14548
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www.fil.ion.ucl.ac.uk www.fil.ion.ucl.ac.uk
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Friston, K. J., Parr, T., Zeidman, P., Razi, A., Flandin, G., Daunizeau, J., Hulme, O. J., Billig, A. J., Litvak, V., Moran, R. J., Price, C. J., & Lambert, C. (2020). Dynamic causal modelling of COVID-19. ArXiv:2004.04463 [q-Bio]. http://arxiv.org/abs/2004.04463
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www.thelancet.com www.thelancet.com
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Zhang, J. et al. (2020, April 2). Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study. The Lancet: Infectious Diseases. https://doi.org/10.1016/S1473-3099(20)30230-9.
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psyarxiv.com psyarxiv.com
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Segovia-Martín, J., & Tamariz, M. (2020, May 5). Testing early and late connectivity dynamics in the lab: an experiment using 4-agent micro-societies. https://doi.org/10.31234/osf.io/nuf78
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Shweta, F., Murugadoss, K., Awasthi, S., Venkatakrishnan, A., Puranik, A., Kang, M., Pickering, B. W., O’Horo, J. C., Bauer, P. R., Razonable, R. R., Vergidis, P., Temesgen, Z., Rizza, S., Mahmood, M., Wilson, W. R., Challener, D., Anand, P., Liebers, M., Doctor, Z., … Badley, A. D. (2020). Augmented Curation of Unstructured Clinical Notes from a Massive EHR System Reveals Specific Phenotypic Signature of Impending COVID-19 Diagnosis [Preprint]. Infectious Diseases (except HIV/AIDS). https://doi.org/10.1101/2020.04.19.20067660
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psyarxiv.com psyarxiv.com
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Rotella, A. M., & Mishra, S. (2020, April 24). Personal relative deprivation negatively predicts engagement in group decision-making. https://doi.org/10.31234/osf.io/6d35w
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link.aps.org link.aps.org
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Krönke, J., Wunderling, N., Winkelmann, R., Staal, A., Stumpf, B., Tuinenburg, O. A., & Donges, J. F. (2020). Dynamics of tipping cascades on complex networks. Physical Review E, 101(4), 042311. https://doi.org/10.1103/PhysRevE.101.042311
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- Apr 2020
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Leitner, S. (2020, April 18). On the dynamics emerging from pandemics and infodemics. https://doi.org/10.31234/osf.io/nqru6
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Han, L., Lin, Z., Tang, M., Zhou, J., Zou, Y., & Guan, S. (2020). Impact of contact preference on social contagions on complex networks. Physical Review E, 101(4), 042308. https://doi.org/10.1103/PhysRevE.101.042308
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journals.plos.org journals.plos.org
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Garira W (2020) The research and development process for multiscale models of infectious disease systems. PLoS Comput Biol 16(4): e1007734. https://doi.org/10.1371/journal.pcbi.1007734
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www.thelancet.com www.thelancet.com
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Xu, S., & Li, Y. (2020). Beware of the second wave of COVID-19. The Lancet, S014067362030845X. https://doi.org/10.1016/S0140-6736(20)30845-X
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Government of Canada. (2020). Government of Canada funds 49 additional COVID-19 research projects – Details of the funded projects. Canada.ca. https://www.canada.ca/en/institutes-health-research/news/2020/03/government-of-canada-funds-49-additional-covid-19-research-projects-details-of-the-funded-projects.html
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Noorazar, H. (2020). Recent advances in opinion propagation dynamics: A 2020 Survey. ArXiv:2004.05286 [Physics]. http://arxiv.org/abs/2004.05286
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arxiv.org arxiv.org
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Nanni, M., Andrienko, G., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Giannotti, F., Guidotti, R., Helbing, D., Kertesz, J., Lehmann, S., Lepri, B., Lukowicz, P., … Vespignani, A. (2020). Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. ArXiv:2004.05222 [Cs]. http://arxiv.org/abs/2004.05222
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marlin-prod.literatumonline.com marlin-prod.literatumonline.com
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Liao, H., Zhang, L., Marley, G., Tang, W. (2020). Differentiating COVID-19 response strategies. University of North Carolina Project-China. DOI: 10.1016/j.xinn.2020.04.003
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doi.org doi.org
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Atchison, C. J., Bowman, L., Vrinten, C., Redd, R., Pristera, P., Eaton, J. W., & Ward, H. (2020). Perceptions and behavioural responses of the general public during the COVID-19 pandemic: A cross-sectional survey of UK Adults [Preprint]. Public and Global Health. https://doi.org/10.1101/2020.04.01.20050039
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www.pnas.org www.pnas.org
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Stavroglou, S. K., Pantelous, A. A., Stanley, H. E., & Zuev, K. M. (2020). Unveiling causal interactions in complex systems. Proceedings of the National Academy of Sciences, 117(14), 7599–7605. https://doi.org/10.1073/pnas.1918269117
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- Mar 2020
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www.mdanalysis.org www.mdanalysis.org
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MDAnalysis
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- Oct 2019
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www.iste.co.uk www.iste.co.uk
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Time and Dynamics
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- Jun 2019
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blogs.psychcentral.com blogs.psychcentral.com
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Internalization of anger can cause heart problems. As the Levenson study above shows, holding in your anger takes a toll on your heart. If you grow up in a household that is intolerant of your anger, ignores your anger, or fails to name, discuss or validate the reasons for your anger, you learn only one way to deal with it: wall it off. This may allow you to cope as a child, but it can harm your heart. Sensitivity to stress can cause back problems or headaches. What makes you sensitive to stress? Not dealing with your feelings. When you wall off your fear, your insecurity, your uncertainty, your anger, sadness, or hurt, those feelings do not go away. They simply pool together on the other side of the wall, waiting for something to touch them off. Then, when it happens, they all surge at you, making you feel overwhelmed and stressed. So going through your life with your feelings blocked makes you more sensitive to stress. Lack of self-awareness makes you vulnerable to poor habits. Families who don’t notice what their child is feeling miss getting to know their child on a deeply personal level. So they sadly remain unaware of who their child really is. I have seen, over decades of treating Childhood Emotional Neglect, that if your parents don’t see you, you do not learn that you are worth looking at. You grow up to be unaware of your own needs, and deep down you don’t realize that your needs even matter. You then are vulnerable to eating or sleeping too much or too little, drinking too much, or engaging in other behaviors that can harm your health. 3 Steps to Stop Childhood Emotional Neglect (CEN) From Harming Your Health Start paying attention to your feelings as you go through your day. Learn more emotion words and make an effort to use them, including naming your own feelings see the book Running On Empty: Overcome Your Childhood Emotional Neglect for an exhaustive list of feeling words). As you do steps 1 and 2 you will start to feel more. Now it is time to begin to actively take charge of your feelings. Work on learning the emotion s
IT should also be stressed that family dysfunction is highly variable and study correlations should never be construed as simple cause and effect. None of it is that simple--especially when it comes to dysfunctional family dynamics.Serious abusers for instance are expert liars (lest outsiders shine light on their true nature), and many come to clinic with stress related complaints about their own childhood experiences. Therapists and other healers must keep that in mind, and not fall to the flattery of 'so-and-so' is so good and helped me so much," while concealing and denying ongoing abuse they may be passing on--some in frank denial--on to their own families and to their own children.
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- Nov 2018
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www.microsoft.com www.microsoft.com
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Holographic computing made possible
Microsoft hololens is designed to enable a new dimension of future productivity with the introduction of this self-contained holographic tools. The tool allows for engagement in holograms in the world around you.
Learning environments will gain ground with the implementation of this future tool in the learning program and models.
RATING: 5/5 (rating based upon a score system 1 to 5, 1= lowest 5=highest in terms of content, veracity, easiness of use etc.)
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- Jul 2018
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wendynorris.com wendynorris.com
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er. Each of these choices reflect power dynamics and conflicting tensions. Desires for ‘presence’ or singular focus often conflict with obligations to be responsive and integrate ‘work’ and ‘life
Are these power dynamics/tensions: actor or agent-based? individual or technical? situational or contextual? deliberate or autonomous?
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- Aug 2017
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Microsoft Dynamics CRM Training
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- Jan 2017
- Sep 2015
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cms.whittier.edu cms.whittier.edu
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Another key area of research has focused on the relationship between individual or group identity and housing
Depending on how many people are involved in the use of an area, the dynamics can change
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- Jan 2014
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en.wikioffuture.org en.wikioffuture.org
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intra-individual concordance
Are there examples of this kind of data product at scale?
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but scientists' understanding of the emergent spatial dynamics at the population level has not kept pace, in large part due to an absence of appropriate tools for data handling and statistical analysis.
Tools gap needs to be filled to improve understanding of emergent spatial dynamics.
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A grant is awarded to University of Maryland, College Park to develop informatics tools that allow scientists and conservation managers to use animal relocation and tracking data to study movement processes at the population level.
Movement Dynamics Homepage: http://www.clfs.umd.edu/biology/faganlab/movement/
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www.clfs.umd.edu www.clfs.umd.edu
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NSF Advances in Biological Informatics: "Informatics tools for population-level animal movements." with T. Mueller, P. Leimgruber, A. Royle, and J. Calabrese. Thomas Mueller, an Assistant Research Scientist in my lab, leads this project. Also on this grant, postdoc Chris Fleming is investigating theoretical aspects of animal foraging and statistical issues associated with empirical data on animal movements. This project is developing innovative data management and analysis tools that will allow scientists and conservation managers to use animal relocation and tracking data to study movement processes at the population-level, focusing on the interrelationship of multiple moving individuals. We are developing and testing these new tools using datasets on Mongolian gazelles, whooping cranes, and blacktip sharks. More information is available on the Movement Dynamics Homepage.
Movement Dynamics Homepage: http://www.clfs.umd.edu/biology/faganlab/movement/
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www.clfs.umd.edu www.clfs.umd.edu
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My project seeks to develop computer models that simulate and link behavioral movement mechanisms which can be either based on memory, perceptual cues or triggered by environmental factors. It explores their efficiency under different scenarios of resource distributions across time and space. Finally it tries to integrate empirical data on resource distributions as well as movements of moving animals, such as satellite data on primary productivity and satellite tracking data of Mongolian gazelles.
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