Perhaps a sort of protobuf is better.

I came here after recalling a critique by Bessel van der Kolk's "The Body Keeps the Score: Brain, Mind, and Body in the Healing of Trauma" regarding the disease model and it's negative impact on adequately helping people with trauma. van der Kolk's critique was similar to Marc Lewis' critique of the disease model as it applies to addiction from "The Biology of Desire: Why Addiction Is Not a Disease". This made me wonder what the term "disease" actually means and whether or not some general consensus existed within the medical community. This article suggests there is no such consensus.

This article is by Jackie Leach Scully who holds a "PhD in cellular pathology, University of Cambridge; BA (Hons) in biochemistry, University of Oxford; MA in psychoanalytic studies, Sheffield University".

Scully does several insightful things in this paper the following are the ones that were most salient to me upon the first read: - distinguishes "disease" from "disability" - contrasts the "social model" and "medical model" perspectives on "disability" - The "medical model" referred to here is probably what Lewis & van der Kolk are critiquing as the "disease model".<br /> - Are the "medical" and "disease" model different? - the social model seems to have arisen as a response to the inadequacy of the medical model

    - "The social model's fundamental criticism of the medical model is that it wrongly locates 'the problem' of disability in biological constraints, considering it only from the point of view of the individual and neglecting the social and systemic frameworks that contribute to it. The social model distinguishes between impairment (the biological substrate, such as impaired hearing) and the disabled experience. In this view the presence of impaired hearing is one thing, while the absence of subtitling on TV is quite another, and it is the refusal of society to make the necessary accommodations that is the real site of disability. A social model does not ignore biology, but contends that societal, economic and environmental factors are at least as important in producing disability."

• brings up a subtle point that there are two jumps "from gene to phenotype, and from phenotype to experience" and that some of the arguments mentioned "suggest that the 'harm' of the impairment is not straightforwardly related to phenotype. What ought to concern us about disease and disability is the disadvantage, pain or suffering involved, and in a sense the impairment is always a kind of surrogate marker for this experience."

Kan, U., Feng, M., & Porter, M. A. (2021). An Adaptive Bounded-Confidence Model of Opinion Dynamics on Networks. ArXiv:2112.05856 [Physics]. http://arxiv.org/abs/2112.05856

Bagheri, G., Thiede, B., Hejazi, B., Schlenczek, O., & Bodenschatz, E. (2021). An upper bound on one-to-one exposure to infectious human respiratory particles. Proceedings of the National Academy of Sciences, 118(49). https://doi.org/10.1073/pnas.2110117118

Al-Hasan, A., Khuntia, J., & Yim, D. (2021). Does Seeing What Others Do Through Social Media Influence Vaccine Uptake and Help in the Herd Immunity Through Vaccination? A Cross-Sectional Analysis. Frontiers in Public Health, 9, 1668. https://doi.org/10.3389/fpubh.2021.715931

Adler, J. M., & Wang, K. (2021). Narrative identity among people with disabilities during the COVID-19 pandemic: The interdependent self. PsyArXiv. https://doi.org/10.31234/osf.io/6724x

A proposal to use decentralized blockchain to make large scale coordination possible.

Pennycook, G., & Rand, D. (2021). Nudging social media sharing towards accuracy. PsyArXiv. https://doi.org/10.31234/osf.io/tp6vy

Stop Reset Go

How do we engage in bottom-up whole system change? Perhaps we need a model for understanding who we are serving that transcends the bias and limitations of personas as they are used in user experience design (UX).

What is a more holistic model for understanding human perceptions, motivations, and behaviours?

Constant, A., Conserve, D. F., Gallopel-Morvan, K., & Raude, J. (2021). Acceptance of COVID-19 preventive measures as a tradeoff between health and social outcomes. PsyArXiv. https://doi.org/10.31234/osf.io/ytz8p

Sadus, K., Göttmann, J., & Schubert, A.-L. (2021). Predictors of stockpiling behavior during the COVID-19 pandemic in Germany [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/2m9nu

Yasseri, T., & Menczer, F. (2021). Can the Wikipedia moderation model rescue the social marketplace of ideas? ArXiv:2104.13754 [Physics]. http://arxiv.org/abs/2104.13754

Ortiz, E., & Serrano, M. Á. (2021). Multiscale opinion dynamics on real networks. ArXiv:2107.06656 [Physics]. http://arxiv.org/abs/2107.06656

Romero, P., Mikiya, Y., Nakatsuma, T., Fitz, S., & Koch, T. (2021). Modelling Personality Change During Extreme Exogenous Conditions. PsyArXiv. https://doi.org/10.31234/osf.io/rtmjw

Aleta, A., Martín-Corral, D., Pastore y Piontti, A., Ajelli, M., Litvinova, M., Chinazzi, M., Dean, N. E., Halloran, M. E., Longini Jr, I. M., Merler, S., Pentland, A., Vespignani, A., Moro, E., & Moreno, Y. (2020). Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19. Nature Human Behaviour, 1–8. https://doi.org/10.1038/s41562-020-0931-9

Peter Sheridan Dodds. (2021, March 7). The map is not the territory. And the mapmakers are not the map. [Tweet]. @peterdodds. https://twitter.com/peterdodds/status/1368559285182099463

Oraby, T., Thampi, V., & Bauch, C. T. (2014). The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases. Proceedings of the Royal Society B: Biological Sciences, 281(1780). https://doi.org/10.1098/rspb.2013.3172

Kozlowski, Diego, Jennifer Dusdal, Jun Pang, and Andreas Zilian. ‘Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation’. ArXiv:2011.02887 [Physics], 5 November 2020. http://arxiv.org/abs/2011.02887.

McKenna, S. (n.d.). COVID Models Show How to Avoid Future Lockdowns. Scientific American. Retrieved 26 February 2021, from https://www.scientificamerican.com/article/covid-models-show-how-to-avoid-future-lockdowns/

Wang, X., Sirianni, A. D., Tang, S., Zheng, Z., & Fu, F. (2020). Public Discourse and Social Network Echo Chambers Driven by Socio-Cognitive Biases. Physical Review X, 10(4), 041042. https://doi.org/10.1103/PhysRevX.10.041042

Anderson, S. C., Edwards, A. M., Yerlanov, M., Mulberry, N., Stockdale, J. E., Iyaniwura, S. A., Falcao, R. C., Otterstatter, M. C., Irvine, M. A., Janjua, N. Z., Coombs, D., & Colijn, C. (2020). Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing. PLOS Computational Biology, 16(12), e1008274. https://doi.org/10.1371/journal.pcbi.1008274

Stewart, A. J., McCarty, N., & Bryson, J. J. (2020). Polarization under rising inequality and economic decline. Science Advances, 6(50), eabd4201. https://doi.org/10.1126/sciadv.abd4201

Hickok, A., Kureh, Y., Brooks, H. Z., Feng, M., & Porter, M. A. (2021). A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs. ArXiv:2102.06825 [Nlin, Physics:Physics]. http://arxiv.org/abs/2102.06825

Aminpour, P., Gray, S. A., Singer, A., Scyphers, S. B., Jetter, A. J., Jordan, R., Murphy, R., & Grabowski, J. H. (2021). The diversity bonus in pooling local knowledge about complex problems. Proceedings of the National Academy of Sciences, 118(5). https://doi.org/10.1073/pnas.2016887118

Tepper, S., & Neil Lewis, J. (2021). When the Going Gets Tough, How Do We Perceive the Future? PsyArXiv. https://doi.org/10.31234/osf.io/pkaxn

Donsimoni. J. R., Glawion. R., Plachter. B., Walde. K., (2020). Projecting the Spread of COVID-19 for Germany. Institute of labor economics. Retrieved from: https://covid-19.iza.org/publications/dp13094/

Shi, W., Wang, L., & Qin, J. (2020). Extracting user influence from ratings and trust for rating prediction in recommendations. Scientific Reports, 10(1), 13592. https://doi.org/10.1038/s41598-020-70350-1

Engelhardt, R., Hendricks, V. F., & Stærk-Østergaard, J. (2020). The Wisdom and Persuadability of Threads. ArXiv:2008.05203 [Physics]. http://arxiv.org/abs/2008.05203

Atkeson, A. (2020). What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios (Working Paper No. 26867; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w26867

Allcott, H., Boxell, L., Conway, J. C., Gentzkow, M., Thaler, M., & Yang, D. Y. (2020). Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic (Working Paper No. 26946; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w26946

Avery, C., Bossert, W., Clark, A., Ellison, G., & Ellison, S. F. (2020). Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists (Working Paper No. 27007; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27007

Razin, A., Sadka, E., & Schwemmer, A. H. (2020). DEglobalizaion and Social Safety Nets in Post-Covid-19 Era: Textbook Macroeconomic Analysis (Working Paper No. 27239; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27239

Alfaro, L., Faia, E., Lamersdorf, N., & Saidi, F. (2020). Social Interactions in Pandemics: Fear, Altruism, and Reciprocity (Working Paper No. 27134; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27134

Stock, James H. ‘Data Gaps and the Policy Response to the Novel Coronavirus’. Working Paper. Working Paper Series. National Bureau of Economic Research, March 2020. https://doi.org/10.3386/w26902.

Malani, A., Soman, S., Asher, S., Novosad, P., Imbert, C., Tandel, V., Agarwal, A., Alomar, A., Sarker, A., Shah, D., Shen, D., Gruber, J., Sachdeva, S., Kaiser, D., & Bettencourt, L. M. A. (2020). Adaptive Control of COVID-19 Outbreaks in India: Local, Gradual, and Trigger-based Exit Paths from Lockdown (Working Paper No. 27532; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27532

Bethune, Z. A., & Korinek, A. (2020). Covid-19 Infection Externalities: Trading Off Lives vs. Livelihoods (Working Paper No. 27009; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27009

Galbadage, T., Peterson, B. M., Wang, D. C., Wang, J. S., & Gunasekera, R. S. (2020). Biopsychosocial and Spiritual Implications of Patients with COVID-19 Dying in Isolation [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/7um3x

Acemoglu, D., Chernozhukov, V., Werning, I., & Whinston, M. D. (2020). Optimal Targeted Lockdowns in a Multi-Group SIR Model (Working Paper No. 27102; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27102

Baqaee, D., Farhi, E., Mina, M. J., & Stock, J. H. (2020). Reopening Scenarios (Working Paper No. 27244; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27244

Gupta, S., Montenovo, L., Nguyen, T. D., Rojas, F. L., Schmutte, I. M., Simon, K. I., Weinberg, B. A., & Wing, C. (2020). Effects of Social Distancing Policy on Labor Market Outcomes (Working Paper No. 27280; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27280

Block, P., Hoffman, M., Raabe, I. J., Dowd, J. B., Rahal, C., Kashyap, R., & Mills, M. C. (2020). Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world. Nature Human Behaviour, 4(6), 588–596. https://doi.org/10.1038/s41562-020-0898-6

Gibson Miller, J., Hartman, T. K., Levita, L., Martinez, A. P., Mason, L., McBride, O., … Bentall, R. (2020, April 20). Capability, opportunity and motivation to enact hygienic practices in the early stages of the COVID-19 outbreak in the UK. https://doi.org/10.31234/osf.io/typqv

Freeston, M. H., Tiplady, A., Mawn, L., Bottesi, G., & Thwaites, S. (2020, April 14). Towards a model of uncertainty distress in the context of Coronavirus (Covid-19). https://doi.org/10.31234/osf.io/v8q6m

Golino, H., Christensen, A. P., Moulder, R. G., Kim, S., & Boker, S. M. (2020, April 14). Modeling latent topics in social media using Dynamic Exploratory Graph Analysis: The case of the right-wing and left-wing trolls in the 2016 US elections. https://doi.org/10.31234/osf.io/tfs7c

Toxvaerd, F. M. O. (2020). Equilibrium Social Distancing [Working Paper]. Faculty of Economics, University of Cambridge. https://doi.org/10.17863/CAM.52489

West, R., Michie, S., Rubin, G. J., & Amlôt, R. (2020). Applying principles of behaviour change to reduce SARS-CoV-2 transmission. Nature Human Behaviour, 1–9. https://doi.org/10.1038/s41562-020-0887-9

Fan, R., Xu, K., & Zhao, J. (2020). Weak ties strengthen anger contagion in social media. ArXiv:2005.01924 [Cs]. http://arxiv.org/abs/2005.01924

Pham, T. M., Kondor, I., Hanel, R., & Thurner, S. (2020). The effect of social balance on social fragmentation. ArXiv:2005.01815 [Nlin, Physics:Physics]. http://arxiv.org/abs/2005.01815

Britwum, K., Catrone, R., Smith, G. D., & Koch, D. S. (2020, May 5). A University Based Social Services Parent Training Model: A Telehealth Adaptation During the COVID-19 Pandemic. https://doi.org/10.31234/osf.io/gw3cd

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

Moya, M., Willis, G. B., Paez, D., Pérez, J. A., Gómez, Á., Sabucedo, J. M., … Salanova, M. (2020, April 23). La Psicología Social ante el COVID19: Monográfico del International Journal of Social Psychology (Revista de Psicología Social). https://doi.org/10.31234/osf.io/fdn32

Lades, L., Laffan, K., Daly, M., & Delaney, L. (2020, April 22). Daily emotional well-being during the COVID-19 pandemic. https://doi.org/10.31234/osf.io/pg6bw

Colombo, R., Wallace, M., & Taylor, R. S. (2020, April 11). An Essential Service Decision Model for Applied Behavior Analytic Providers During Crisis. https://doi.org/10.31234/osf.io/te8ha

Rafiei, F., & Rahnev, D. (2020, April 9). Does the diffusion model account for the effects of speed-accuracy tradeoff on response times?. https://doi.org/10.31234/osf.io/bhj85