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Social sorting is understood as the breakdown and categorization of group- or person-related raw data into various categories and segments by data manipulators and data brokers[citation needed]. Social sorting involves the key task of separating one group from the other[citation needed]. These groups can be based on income, education, race, ethnicity, gender, occupation, social status, derived power (social and political) and geographic residence[citation needed]. Depending on the goals of the manipulator raw data is collected and then further evolves into meaningful data in order to be exploited for a specific purpose[citation needed]. For example, the formulation of profiling and predictive policing are all derivations of social sorting[citation needed].
History
editThe concept is accredited to David Lyon, a sociologist who is best known for his work in surveillance studies[citation needed].
Themes
editCriticisms are often directed at the laws, implemented rules, educational system, job employment opportunities and at the government[citation needed]. Questions are asked of the integrity of many socially constructed programs led by private and government institutions[citation needed].
The September 11 attacks and the subsequent war on terror have fueled the desire for categorizing and profiling people[citation needed]. The beneficiaries that are associated with it[clarification needed] are evident as it allows for a more transparent viewership[who?]. Some researchers such as David Lyon are concerned with the rise of big data as there are many implication on the daily lives of many[citation needed].
According to David Lyon, Canadians are still unaware of the fact that surveillance which goes collaboratively with social sorting is now very much integrated into their daily lives[citation needed]. David Lyon discusses that the systematic routines and attention to personal detail which is encompassed into surveillance[citation needed]. The key criticism[clarification needed] involves indifferent treatment to individuals based on their profile[citation needed]. Depending on the details of a person it can lead to the determination of whether the person may end up on a No Fly List.
David Lyon insinuates that social sorting through surveillance is a modern threat to freedom[citation needed]. Byproducts of social sorting are isolation, segregation and marginalization[citation needed]. Social sorting has highlighted issues that primarily involve equity and fairness[citation needed].
Wilson & McBrier (2005) conducted a longitudinal study based on the theory of minority vulnerability of employees.[1] These constitute to a group of African Americans who work for good financial income in the upper tier for relatively privileged jobs. "The minority vulnerability thesis, accordingly, maintains that African Americans are more likely to experience layoffs from upper-tier occupations than Whites even when the two groups have similar background socioeconomic statuses, have accumulated similar human-capital credentials, such as educational attainment and commitment to work, and have similar job/labor market characteristics, including union status as well as economic sector of employment. Findings indicate that, after controlling for seniority, African Americans are susceptible to layoffs on a relatively broad and generalized basis that is unstructured by traditional, stratification-based causal factors, namely, background socioeconomic status, human-capital credentials, and job/labor-market characteristics."
In 2015, The Data Broker Accountability and Transparency Act was resurrected by four U.S senators that would allow consumers to see and correct personal information held by data brokers and tell those businesses to stop sharing or selling it for marketing purposes[citation needed].
See also
editReferences and further reading
edit- ^ George Wilson and Debra Branch McBrier (2005). "Race and Loss of Privilege: African American/White Differences in the Determinants of Job Layoffs From Upper-Tier Occupations". Sociological Forum. 20 (2): 301–321. doi:10.1007/s11206-005-4102-6. S2CID 144509770.
- Biesele, M. 1993. Women Like Meat. The folklore and foraging ideology of the Kalahari Ju/'hoan. Witwatersrand: University Press.
- http://www.espncricinfo.com/southafrica/content/story/863161.html
- http://journals1.scholarsportal.info/pdf/08848971/v20i0002/301_ralopaojlfuo.xml[full citation needed]
- http://cognet.mit.edu/book/sorting-things-out
- https://www.youtube.com/watch?v=xtAa-f-1rTg
- http://www.universityaffairs.ca/news/news-article/researchers-concerned-by-the-rise-of-big-data-surveillance/
- http://www.computerworld.com/article/2893693/lawmakers-target-data-brokers-in-privacy-bill.html