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I am interested in the Macro scale and the macro effects evident at a city-scale level. I remember visiting New Orleans in 2016 and vividly remember seeing several signs with a large 'No' symbol drawn and the text  "neighbors not tourists" printed on the sign. Recently, as part of my research into New Orleans, I stumbled on this piece by the Guardian on how short-term rentals through platforms such as Airbnb are leading to gentrification in New Orleans. Highlighted in the article is how several Airbnb hosts do not reside on the listed premises. I remember the place we stayed, as we were a large party, having a 617 prefix number.  The prefix stood out as I knew the code 617 represented Boston and was curious what someone with ties to Boston doing in New Orleans as a host. In a similar vein, the article also highlights the problem of absentee hosts, hosts who acquire property for the sole purpose of setting up the property as an Airbnb site.

To tackle the problem, one councilwoman passed a law that required any Airbnb hosts in residential zones to have a homestead exemption verifying they live on site. In this case, a city-wide measure was taken and passed into law affecting the micro. It is common to have one host having several properties in different residential areas in New Orleans. From a technical standpoint, it could be viewed that Airbnb as technology is developed and presented as a scalable product. With no limits to reproducibility. Meanwhile, real-life discontinuities exist in the form of such homestead laws. It is impossible to live in more than one homestead at the same time. In other words, the concept of the human is not scalable.
Likewise, neither is cultural heritage. The city of New Orleans positions its self as a city with great cultural heritage. It is through this heritage that they seek to draw more and more tourists. How do cities think of scaling up successful initiatives and how do they navigate the political, social, ecological, or economic entanglements. At what point is downscaling necessary? Is culture scalable?

[1]https://www.theguardian.com/us-news/2019/mar/13/new-orleans-airbnb-trem…

I am currently a Ph.D. student interested in exploring the entanglements of scale, especially in the context of environmental sensing.  My primary research seeks to engage in discourse around the value of scalability that is presented as inherent in computation. While the term scale-up is almost synonymous with computation, sustainability; on the other hand, is known as a problem of scale. Take for example, the discourse on climate change where the actions required to combat climate change requires interventions at different scales. In this context, demanding changes at individual scales while no corresponding changes happen at larger scales would not yield much.

In looking at New Orleans, I came across a video on IoT cameras developed by Cisco, the networking giant. What struck me other than the apparent rise of surveillance capitalism was the narrative of one of the police officers highlighted in the video. The officer mentions that it is not feasible for the city to place police officers on every corner. In the context of scale, the police officer is implying that cameras are useful as they extend the police officer's ability to surveil the city. In other words, cameras and the networks help scale up the police officer, making it possible for them to cover a larger scale than before.

One of the police officers, in the video, also mentions that New Orleans is a tourist and hospitable town. Which brings up the question at any given period, what scale of visitors can New Orleans support without stretching the city's resources? Several other cities in the world have made efforts to limit visitors, in order not stretch city resources. The recent crisis at Mount Everest is an excellent example of what happens when resources are stretched to accommodate the increasing number of local visitors. How could something of this nature similarly impact New Orleans?

At the communication center where the video feed is analyzed, the IT manager provides reasons as to why they chose Cisco as their vendor. One of the reasons he gives was that the system is easily expandable, allowing the ability to scale out/up the network.

The primary method of supporting the main argument is a series of historical examples including policies such as those created by the World Health Organization, outbreaks including AIDS, and previous attempts to provide health security such as the Smallpox Caccination Program. The use of these examples highlights the changing nature of health problems and how that effects the type health security. Specific dates and data from the examples is included, which allows for a more detailed analysis to support the main argument. 

Users input contact data and video recordings

This policy addresses public health in that it can reduce the amount of time between a 911 call and the start of patient care if the EMS responders feel more comfortable entering a scene before police arrive. 

The author, Didier Fassin, is a French anthropologist and sociologist with training in medicine and public health. He has worked in the field of medical anthropology for decades through research and field experience. He currently works as a professor of social science at the Institute for Advanced Study in Princeton. 

The system has partners including UNAIDS, a branch of UNISEF, International Medical Corps, Medecins Du Monde, AAHI, and other humanitarian organizations. The support of these groups both financially and with the user community is important to maintain the app as an active site for research and development. The technical aspects of the site also heavily rely on the data storage method, which is not mentioned but would require massive amounts of memory as well as safeguards to prevent data loss on the app servers.

Different sections of the policy applies to different groups, the first section focused on disaster preparedness which was directed at state and city governments. The subsequent sections apply to various organizations and government groups that would be working under an interagency task force in the case of an emergency, and the individuals that would be requesting aid or funding after a disaster.