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Porter, T. M. (1996). Trust in numbers: the pursuit of objectivity in science and public life (p. 324). Princeton University Press. Retrieved from http://books.google.com/books?id=_3OZN-eaC-0C&pgis=1
Porter, T. M. (2009). The Culture of Quantification and the History of Public Reason. Journal of the History of Economic Thought, 26(02), 165. doi:10.1080/1042771042000219019
Porter, T., & Porter, T. M. (1994). Information, Power, and the View from Nowhere. In L. Bud-Frierman (Ed.), Information Acumen: The Understanding and Use of Knowledge in Modern Business (pp. 217â230). London: Routledge.
To draw an analogy with computer coding, we might say that financial instruments are analogous to âhigh-levelâ programming languages such as Java or Ruby: they let you string commands together in order to perform certain actions. You want to get resources from A to B over time? Well, we can...

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By taking human decisionmaking out of the equation, weâre slowly stripping away deliberationâmoments where we reflect on the morality of our actions.
(via Relying on Algorithms and Bots Can Be Really, Really Dangerous | by Clive Thompson, Wired Opinion | Wired.com)
Q: HOW CAN BIG DATA HAVE A SOCIAL IMPACT?
Big Data has the potential to transform development and accelerate social progress around the world, but there are issues surrounding understanding, ownership, privacy, capacity, measurement and more that need further dialogue and discussion. The Skoll World Forum on Social Entrepreneurship partnered with the HBR-The Bridgespan Group Insight Center on Scaling Social Impact to surface key insights and practical lessons in harnessing the power of data for large-scale social impact. This debate will also set the stage for a larger discussion on the topic at this yearâs Skoll World Forum in Oxford, UK.
Letâs give credit where it is due: Google is not hiding its revolutionary ambitions. As its co-founder Larry Page put it in 2004, eventually its search function âwill be included in peopleâs brainsâ so that âwhen you think about something and donât really know much about it, you will automatically get informationâ.
Science fiction? The implant is a rhetorical flourish but Mr Pageâs utopian project is not a distant dream. In reality, the implant does not have be connected to our brains. We carry it in our pockets â itâs called a smartphone.
resisting being quantified makes you unpredictable to systems that make predictions based on facts.
@Infovore Âť 21st-century camouflage
Moral Information Processing
Moral information processing has to do with how people comprehend moral events in stories, activities and in real life. We have studied moral information processing or moral discourse processing with story comprehension (theme comprehension, recall, ratings of importance of story events, inferences made while reading) and with videogame effects on finishing stories. See Narvaez (2002) for a review of individual difference effects on processing.
 Published Papers
 Narvaez, D. (1998).  The effects of moral schemas on the reconstruction of moral narratives in 8th grade and college students.  Journal of Educational Psychology, 90(1), 13-24.
 Narvaez, D., Bentley, J., Gleason, T., Samuels, J. (1998).  Moral theme comprehension in third grade, fifth grade and college students. Reading Psychology, 19(2), 217-241.
 Narvaez, D., & Mitchell, C. (1999). Schemas, culture, and moral texts. (In M. Leicester, C. Modgil, & S. Modgil, Eds.) Education, Culture and Values (Vol. IV of Moral Education and Pluralism) (pp. 149-157). London: Falmer Press.
 Narvaez, D., van den Broek, P., and Ruiz, A. (1999). Reading purpose, type of text and their influence on think-aloud and comprehension measures. Journal of Educational Psychology, 91(3), 488-496.
 Narvaez, D., Gleason, T., Mitchell, C. & Bentley, J. (1999). Moral theme comprehension in children. Journal of Educational Psychology, 91(3), 477-487.
              Reprinted in D. Boyd & G. Stevens (Ed.), Current Readings in Lifespan Development (pp. 73-87). Allyn & Bacon.
 Narvaez, D. (1999). Using discourse processing methods to study moral thinking. Educational Psychology Review, 11 (4), 377-394.
  Rest, J. R., Narvaez, D., Bebeau, M., & Thoma, S. (2000). A neo-Kohlbergian approach to morality research. Journal of Moral Education, 29 (4), 381-395.
             Reprinted in Mason, M. (2004). Taking Sides: Clashing Views on Controversial Issues in Cognitive Science. McGraw-Hill.
Narvaez, D. (2001).  Moral text comprehension: Implications for education and research.  Journal of Moral Education, 30 (1), 43-54.
 Narvaez, D. (2002). Individual differences that influence reading comprehension. In M. Pressley & C. C. Block (Eds.), Reading Comprehension Instruction (pp. 158-175). New York: Guilford.
 Narvaez, D. (2002). Does reading moral stories build character? Educational Psychology Review 14(2), 155-171.
Narvaez, D. & Bock, T. (2002). Moral schemas and tacit judgement or how the Defining Issues Test is supported by cognitive science.  Journal of Moral Education, 31 (3) 297-314.
Narvaez, D., Lapsley, D., Hagele, S., & Lasky, B. (2006). Moral chronicity and social information processing: Tests of a social cognitive approach to the moral personality.  Journal of Research in Personality, 40, 966â985.
Narvaez, D., & Gleason, T. (2007). The Influence of moral judgment development and moral experience on comprehension of moral narratives and expository texts. The Journal of Genetic Psychology, special issue (Nancy Eisenberg, editor), 168(3), 251â276.
Narvaez, D., Mattan, B., MacMichael, C., & Squillace, M. (2008). Kill bandits, collect gold or save the dying: the effects of playing a prosocial video game. Media Psychology Review. 1 (1).
Narvaez, D., Radvansky, G.A., Lynchard, N., & Copeland, D. (in press). Are older adults more attuned to morally-charged information? Experimental Aging Research
 Narvaez, D., Gleason, T., & Mitchell, C. (in press). Moral virtue and practical wisdom: Theme comprehension in children, youth and adults. Journal of Genetic Psychology.
 Narvaez, D. (in press). The Ethics of Neurobiological Narratives. Poetics Today, special issue on Narrative and the Emotions

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A Timeline of events related to the Deep Web courtesy of Papergirls
1980Â Tim Berners-Lee âdeveloped his first hypertext system, âEnquireâ for his own use (although unaware of the existence of the term HyperText). With a background in text processing, real-time software and communications, Tim decided that high energy physics needed a networked hypertext system and CERN was an ideal site for the development of wide-area hypertext ideas (CERN).â
1989 Tim Berners-Lee started the WorldWideWeb project at CERN.
1992-09Â Arthur Secret at the CERN created the first web gateway to a relational database system RDB (Shestakov 2008-05).
1994 Dr. Jill Ellsworth âfirst coined the phrase âinvisible Webâ to refer to information content that was âinvisibleâ to conventional search engines (Bergman 2001 citing Garcia 1996).â See also
1996 Frank Garcia (1996) claimed Texas-based university professor Jill H. Ellsworth (d.2002), Internet consultant for Fortune 500 companies, coined the term âInvisible Webâ in 1996 to refer to websites that are not registered with any search engine. â âEllsworth is co-author with her husband, Matthew V. Ellsworth, of The Internet Business Book (John Wiley & Sons, Inc., 1994), Marketing on the Internet: Multimedia Strategies for the World Wide Web (John Wiley & Sons, Inc.), and Using CompuServe. She has also explored education on the Internet, and contributed chapters on business and education to the massive tome, The Internet Unleashed.â
[S]igns of an unsuccessful or poor site are easily identified, says Jill Ellsworth. âWithout picking on any particular sites, Iâll give you a couple of characteristics. It would be a site thatâs possibly reasonably designed, but they didnât bother to register it with any of the search engines. So, no one can find them! Youâre hidden. I call that the invisible Web. Ellsworth also makes reference to the âdead Web,â which no one has visited for a long time, and which hasnât been regularly updated (Garcia 1996).
1996-12-01 âThe first commercial Deep Web tool (although they referred to it as the âInvisible Webâ) was @1, announced December 12th, 1996 in partnership with large content providers. According to a December 12th, 1996 press release, @1 started with 5.7 terabytes of content which was estimated to be 30 times the size of the nascent World Wide Web. ( âAmerica Online to Place AT1 from PLS in Internet Search Area: New AT1 Service Allows AOL Members to Search âThe Invisible Webâ).âSee (Choi 2008-01-07).â
1996-12-12 âPersonal Library Software, Inc. (PLS), the leading supplier of search and retrieval software to the online publishing industry, ushered in the next generation of Internet search engines with the introduction of a new Internet based service, AT1 which combines the best of PLSâs search, agent and database extraction technology to offer publishers and users something they have never had before: the ability to search for content residing in âhiddenâ databases â those large collections of documents managed by publishers not viewable by Web spiders. AT1 also allows users to create intelligent agents to search newsgroups and websites with E-Mail notification of results (Press release).â
1997 Michael Lesk wrote an unpublished paper entitled âHow much information is there in the world?â], in which he estimated that in 1997, the Library of Congress had between 20 terabytes and 3 petabytes.â See Choi (2008).
1999-02Â Lawrence and Giles (1999) claimed that the publicly indexable World Wide Web (PIW) contained about 800 million pages; the search engine with the largest index, Northern Light, indexed roughly 16% of the publicly indexable World Wide Web; the combined index of 11 large search engines covered (very) roughly 42% of the publicly indexable World Wide Web.
2000-03Â c. 43,000â96,000 Deep Web sites existed (Bergman 2001).
2000-07-26 BrightPlanet released a study documenting the Deep Web (a massive storehouse of databases and information that was invisible to search engines in 2000) claiming that the Deep Web was 500 times larger than the indexed Web accessible by most search engines. BrightPlanet researchers also released their direct-query search technology called LexiBot⢠which automatically identifies, retrieves, qualifies, and classifies content from Deep Web sites. They listed c. 20,000 Deep Web searchable sites. Direct-query search technology that can access searchable databases unlike most search engines, implies that the Invisible Web is not really Invisible just harder to reach.BrightPlanet Unveils the âDeepâ Web: 500 Times Larger than the Existing Web.
2001BrightPlanet
âquantified the size and relevancy of the deep Web in a study based on data collected between March 13 and 30, 2000. Our key findings include: Public information on the deep Web is currently 400 to 550 times larger than the commonly defined World Wide Web; The deep Web contains 7,500 terabytes of information compared to nineteen terabytes of information in the surface Web; The deep Web contains nearly 550 billion individual documents compared to the one billion of the surface Web; More than 200,000 deep Web sites presently exist; Sixty of the largest deep-Web sites collectively contain about 750 terabytes of information â sufficient by themselves to exceed the size of the surface Web forty times; On average, deep Web sites receive fifty per cent greater monthly traffic than surface sites and are more highly linked to than surface sites; however, the typical (median) deep Web site is not well known to the Internet-searching public; The deep Web is the largest growing category of new information on the Internet; Deep Web sites tend to be narrower, with deeper content, than conventional surface sites; Total quality content of the deep Web is 1,000 to 2,000 times greater than that of the surface Web; Deep Web content is highly relevant to every information need, market, and domain; More than half of the deep Web content resides in topic-specific databases; A full ninety-five per cent of the deep Web is publicly accessible information â not subject to fees or subscriptions (Bergman 2001).â
2001 AlltheWeb, public search engine was launched. (AlltheWeb is now owned by Yahoo.com). It was a redesign of Fast (1999-05 to 2001). Fast Search & Transfer is a Microsoft Subsidiary.
2000Â Shestakov (2008) cites Bergman (2001) as the source for the claim that the term deep Web was coined in 2000. Bergman distinguished the Surface Web from the Deep Web using the metaphor of Surface and Deep water fishing or trawling. Deep Web is preferred over the term Invisible Web.
2000 UC-Berkeley Biologist Michael Eisen, Nobel Laureate Harold Varmus and Stanford biochemist Patrick Brown helped start the Public Library of Science, PLoS is a ânonprofit organization of scientists and physicians committed to making the worldâs scientific and medical literature a freely available public resourceâ by encouraging scientists to insist on open-access publishing models rather than being forced to sign over their (often publicly-funded research) to expensive scientific journals. Wright (2004) cited Eisen, Varmus and Brown as examples of scientists who are making making some areas of the Deep Web more accessible to the public.
2001 Raghavan and Garcia-Molina (2001) âpresented an architectural model for a hidden-Web crawler that used key terms provided by users or collected from the query interfaces to query a Web form and crawl the deep Web resources (Choi 2008-01-07).â
2002-02 StumbleUpon began to use human crawlers or human-based computation techniques to uncover data on the Deep Web. Human crawlers can find relevant links that algorithmic crawlers miss (Choi 2008-01-07).â
2002-12Â There were c. 130,000 Deep Web sites (He, Patel, Mitesh, Zhang and Chang 2007, Shestakov 2008).
2003-06-01Â Dorner and Curtis (2003-06-01) conducted a survey (data collected from 2002-12 through 2003-04) of librarians in New Zealand to compare their common user interface software products supplied by vendors: Endeavour, ExLibris, Follet, Fretwell-Downing, Innovative Interfaces, MuseGlobal, OCLC, SIRSI, WebFeat and VTLS. MuseSearch, ENCompass, MetaLib, Single Search and WebFeat received the highest scores in 2003 (Dorner and Curtis 2003-06-01:2). SingleSearch was noted as having the added cost advantage to librairies since it was open access, open source (Dorner and Curtis 2003-06-01:2). In 2002-2003 a successful common user interface technology software should support formats and protocols other than Z39.50 such as OpenURL, HTTP, SQL, XML, MARC, CrossRef, DOI, EAD, Dublin Core and Telnet (Dorner and Curtis 2003-06-01:8).
2004-04Â There were c. 310,000 Deep Web sites (He, Patel, Mitesh, Zhang and Chang 2007, Shestakov 2008).
2004Â Between 2000 and 2004 the Deep Web increased in size by 3-7 times (He, Patel, Mitesh, Zhang and Chang 2007, Shestakov 2008).
2004-03-02 Yahoo announced its Content Acquisition Program users paid for enhanced search coverage by âunlockingâ the deep Web (Wright 2004).
2005Â Yahoo released Yahoo! Subscriptions which searched a few of the Deep Webâs subscription-only web sites.
2005 Ntoulas et al. (2005) âcreated a hidden-Web crawler that automatically generated meaningful queries to issue against search forms. Their crawler generated promising results, but the problem is far from being solved. Since a large amount of useful data and information resides in the deep Web, search engines have begun exploring alternative methods to crawl the deep Web (Choi 2008-01-07).â
The search engine Pipl crawlers can identify, interact and retrieve some information from the deep Web.
Deep Web âsearch engines like CloserLookSearch and Northern Light Group|Northern Light create specialty engines by topic to search the deep Web. Because these engines are narrow in their data focus, they are built to access specified deep Web content by topic. These engines can search dynamic or password protected databases that are otherwise closed to search engines (Choi 2008-01-07).â
Googleâs âSitemap and mod oai are mechanisms that allow search engines and other interested parties to discover deep Web resources on particular Web servers. Both mechanisms allow Web servers to advertise the URLs that are accessible on them, thereby allowing automatic discovery of resources that are not directly linked to the surface Web(Choi 2008-01-07).â
2007-06 WorldWideScience was created to provide access to the Deep Web. When it began it linked to 12 databases from 10 countries. It is a âscience portal developed and maintained by the Office of Scientific and Technical Information (OSTI), an element of the Office of Science within the U.S. Department of Energy. The WorldWideScience Alliance, a partnership consisting of participating member countries provides the governance structure for the WorldWideScience.org portal (RWW).â
2007-07-27 âIndiana University faculty member Javed Mustafa appeared on National Public Radioâs Science Friday, and drawing on information in a published study from University of California, Berkeley entitled âHow much information is there?â, estimated that the deep web consists of about 91,000 terabytes. By contrast, the surface web, which is easily reached by search engines, is only about 167 terabytes. The Library of Congress contains about 11 terabytes, for comparison. Mustafa noted that these numbers were a bit dated and were just rough estimates (Choi 2008-01-07).â
2008-05-14Â ReadWriteWeb contributor Sarah Perez listed a number of âDigital Image Resources on the Deep Web.â
2008-06 WorldWideScience portal to the Deep Web linked to 32 national, scientific databases and portals from 44 different countries. RWW.
2008 Several âDeep Web directories are under development such as OAIster by the University of Michigan, INFOMINE] at the University of California at Riverside andDirectSearch by Gary Price to name a few (Choi 2008-01-07).â
2008-09-22 Infovell launched its research engine for the Deep Web. âAvailable initially on a subscription basis, Infovell gives users access to hard to find, in-depth, expert information spanning Life Sciences, Medicines, Patents, and other reference categories with more to be added over time.â âInfovellâs research engine will be available beginning September 22 as a premium service for individual researchers and corporations who are seeking more affordable access to expert information. The Company is offering a risk-free trial through its website http://www.infovell.com. Later this year, Infovell will be beta-releasing a free version of its research engine on a limited basis for those individuals who want to search the Deep Web but donât have the need for some of the advanced features available in the premium version.â
2009- United States âCongressional Representative John Conyers (D-MI) re-introduced a bill (HR801) that essentially would negate the  National Institutes of Health (NIH) policy concerning depositing research in Open Access (OA) repositories. The bill goes further than prohibiting open access requirements, however, as the bill also prohibits government agencies from obtaining a license to publicly distribute, perform, or display such work by, for example, placing it on the Internet, and would repeal the longstanding âfederal purposeâ doctrine, under which all federal agencies that fund the creation of a copyrighted work reserve the âroyalty-free, nonexclusive right to reproduce, publish, or otherwise use the workâ for any federal purpose. The National Institutes of Health require NIH-funded research to be published in open-access repositories (Doctorwo 2009).â HR801 would benefit for-profit science publishers and increase challenges for making the Deep Web more accessible. See Doctorwo, Cory. 2009-02-16. âScientific publishers get a law introduced to end free publication of govt-funded research.⠝ Boing Boing.Â
In 1994, Dr. Jill Ellsworth first coined the phrase "invisible Web" to refer to information content that was "invisible" to conventional search engines.
White Paper: The Deep Web: Surfacing Hidden Value
so many worms and counter-worms loose in the data-net
The dark side of the internet | Technology | The Guardian
science-fiction author John Brunner in The Shockwave Rider
You canât âprotestâ against Taskrabbit, against Uber, against drones. The conditions of the conversation are binary: youâre either in, or youâre out. Ultracapitalism, ultrahistory, a complete system. Taskrabbit, Uber, drones, high-frequency trading, austerity, and this: the natural endpoint of algorithmic capitalism. Cheap humans. Just-in-time people. A generation inside the machine, so drunk and indebted that it will be their lasting fame. An airbnb of the flesh. Impersonate the machine.
Impersonating the Machine | booktwo.org (via iamdanw)

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[Mail art] has no history, only a present, which was a pun, of course, on present as now, and present as gift. A pun on my own way of giving information and object or whatever, in letter form.
Ray Johnson
Thereâs no memory at Twitter: everything is fleeting. Though that concept may seem daunting to some (archivists, I feel your pain), it also means the content in my feed is an endless stream of new information, either comments on what is happening right now or thoughts about the future. One of the reasons I loved the Internet when I first discovered it in the mid-1990s was that it was a clean slate, a place that welcomed all regardless of your past as you wrote your new life story; where youâd only be judged on your words and your art and your photos going forward.
Why I love Twitter and barely tolerate Facebook â I.M.H.O. â Medium Matt Haughey on twitter. Via An Xiao Mina
WHY I BLOG THIS: another evidence of the difference between bounded and unbounded social media sites.Â