This week we went through three articles about rules and regulation. One is Latour's ‘Where Are the Missing Masses? The Sociology of a FewMundane Artifacts. He talked about the relationship between society and technology. Another is Lessig's Code V2 chapter 7. I will not go through this article here. The last one is Radin's Regulation by contract, regulation by machine. She argues the illegitimacy of Digital Rights Management Systems (DRMS).
I do not gusrantee the accuracy of the content.
Latour - Where Are the Missing Masses?
Latour's this article is quite interesting. I like his humorous language like "you sociologist" and vivid example like the groom, map, and seat belt.
Latour wrote 10 pages about grooms and seat belt. These mundane tracing of detailed stories of human and technology gives us room to see closer about the relationship of society and technology, not only from a broad and structural view.
Here comes the argument:
Will moral vocabulary diminish because of the delegation? Is delegation negative?
Radin - Regulation by contract, regulation by machine
Radin discussed the contracts and the law for intelletucal property. Contract should be a private agreement, backed by the public law. When a conflict happens, people will turn to the state government. However, shrink wrappers, click wrappers, or browser wrappers ask to waive many rights to use their products. Radin's point in this article is that these so-called "contracts" are no longer legal documents on the court.
The law for intellecutal property is to grant someone the projection their knowledge. It is to give incentives to create instead of exclusive rights and prevent someone from using the products.
For example, a lot of developers and researchers scrapped data from websites (including me). It may violate Terms of Service (TOS). Should we make websites unscrappable, or create stronger law to project content on the websites from technical aspect (if it is possible)?
Reference
Latour, B. (1992). 10 ‘‘Where Are the Missing Masses? The Sociology of a FewMundane Artifacts’’.
Lessig, L. (2009). Code: And other laws of cyberspace. ReadHowYouWant. com.
Radin, M. J. (2004). Regulation by contract, regulation by machine. Journal of Institutional and Theoretical Economics JITE, 160(1), 142-156.
This week we went through three articles in the theme of quantifying and calculating. These days we are clear about two different research methods: qualitative and quantitative methods. When you are saying “I’m a qualitative researcher.” There is some value-driven information here. In the world of quantitative research, how numbers work in a holistic way instead of being so polarized?
Espeland and Stevens - A Sociology of Quantification
This article addresses the oversight by analyzing quantification – the production and communication of numbers – as a general sociological phenomenon. It also introduces five sociological dimensions of quantification and call for an ethics of numbers.
Work. The work of collecting data draws our attention to where data comes from.
Reactivity
Discipline.
Authority
Aesthetic. Data visualization. People may have different training in interpreting the graphics.
Measurement intervenes in the social worlds it depicts. Cause people to think and act differently. It changes the dynamics.
Transform individual experiences and events into general categories or characteristics.
Alter relations of power by affecting how resources are distributed.
Create or reinforce categories to conceive human beings.
Then those measures began to control people. Seeing sth is the first step to control it.
Measures that initially designed to describe behavior can be used to judge and control.
Why and when people give authority to numbers, find numbers credible ways of knowing and communicating.
The authority of the information parallels the authority of its handlers in the hierarchy.
The authors are not talking about good or sad. They just suggest that numbers cannot be reduced to a narrow instrumentality but should be its ethics.
Hacking, “Biopower and the Avalanche of Printed Numbers”
Hacking’s this article is pretty interesting, which goes through the history of counting by isolating a certain period 1820s-1840s. At first census was just simple counting, later people created categories and people were fit into a list of categories. appeared and people were conceived into There are two revolutionary history about biopolitics.
A long term revolution was from the counting of sickness of British men to find the law of sickness. Long-term account biopolitics does not have subversive effect because it has little to do with new categories, new ways of conceiving people. There are two factors in the invention of categories of complaints.
One is the fetishism of counting, which brings easily applied categories in terms of to count. For example, classifying people according to their occupations such as “farmers, artists, salaried workers … ”
One is the theoretical and practical reasoning of individual professionals such as doctors. For example, there is an nationally standardized categories of mental disorders which requires doctors to categorize these disorders according to the list. It is ridiculous when you are illegal to die because the reason of death cannot be categorized into the list!
Hacking uses historical methods to draw how the data was collected. His point is to ask people to think about the conceptual schema people created. Some qualitative research method also uses quantitative way to deal with the data. For example, gender is qualitative information but we use 1 or 2 to represent them.
Bouk, How Our Days Became Numbered: Risk and the Rise of the Statistical Individual [Chapter 2]
Life insurance is not fair for African American. They were not offered life insurance, later, even though they had life insurance, they were only offered 2/3 of the benefits. The insurance companies did discriminate, but they did not discriminate against the race but the high rates of high morality. Race just happened to be a cost-effective marker of high morality. Here is a flaw in this prediction model that is the previous trend of morality rate in a certain period could not represent the morality right now. Since the black were no longer slaved, their life span could change also. Bouk’s viewpoint is not only deny the current prediction model like “you’re wrong with the source of data.” but the success of actual reasoning: “If you did it right, it would be fine.”
Reference
Bouk, D. (2015). How our days became numbered: Risk and the rise of the statistical individual. University of Chicago Press.
Espeland, W. N., & Stevens, M. L. (2008). A sociology of quantification. European Journal of Sociology/Archives Européennes de Sociologie, 49(3), 401-436.
Hacking, I. (2015). Biopower and the avalanche of printed numbers. Biopower: Foucault and Beyond, 65-81.
Why Condorcet Jury Theorem is faulty in collective decision making?
This is a summary of the article by David Austin-smith and Jeffrey S.Banks, Information Aggregation, Rationality, and the Condorcet Jury Theorem (see reference at the bottom). We were encouraged to read it before Monday's course. Of course I had a painful time reading it and the summary may not accurately convey the article's intension.
What is Condorcet Jury theorem?
The Condorcet Jury theorem states that under certain conditions, the probability that a collective chooses the correct alternative by majority votes exceeds the probability that any consitituent meamber of the collective would unilaterally choose that alternative. That is to say, majorities are more likely to select the "better" alternatives under uncertainty.
What is the problem?
This theroem has an important but largely implicit assumption that an individual behaves in exactly the same manner as when that individual alone selects the outcome. Actually, sincere behavior is not rational even has a common preference. And sincere voting does not constitute a Nash equilibrium.
You may ask, what is sincere voting? OK, there are three sorts of voting behaviors:
Sincere voting: each individual selects the alternative yielding his or her hightest expected payoff conditional on their signal.
Informative voting: each individual votes for A if and only if receiving a signal s = 0, and B when s = 1.
Rational voting: individual's decision rultes constitute a Nash equilibrium.
Attention: these three voting behaviors are not mutually exclusive.
The authors describe two assumptions:
Sincere voting is informative when one receives a signal that makes him/her think A/B is the true state.
The common prior belief that the true state is A is sufficiently strong that there is only one condition that someone will select B that he/she observes all three individuals' signals as B. (Why they talk about prior belief here? Otherwise how can you use Bayes' method!)
How to prove the claim?
The authors looked at the role the "sincerity" assumption in Jury Theroems with three variations of an extremely simple model.
(I will not introduce the model here because I have to admit I totally can't understand the definition and formula. After all they use the model to explain it and it seems quite interesting. I think I need to learn more about game theory to understand it).
Reference
Austen-Smith, D., & Banks, J. (1996). Information Aggregation, Rationality, and the Condorcet Jury Theorem. The American Political Science Review, 90(1), 34-45. doi:10.2307/2082796
