Feelings of Discontent and the Promise of Middle Range Theory for STS | Geels

Frank W. Geels; Feelings of Discontent and the Promise of Middle Range Theory for Science & Technology Studies (STS); In Science, Technology & Human Values, Volume 32, Issue 6; 2007-11-01; DOI:10.1177/016224390303597; 25 pages; paywall
Teaser: Examples from Technology Dynamics

Abstract

This article critically discusses the state of STS, expressing feelings of discontent regarding four aspects: policy relevance, conceptual language, too much focus on complexity, theoretical styles. Middle range theory is proposed as an alternative, promising avenue. Middle range theories focus on delimited topics, make explicit efforts to combine concepts, and search for abstracted patterns and explanatory mechanisms. The article presents achievements in that direction for technology dynamics, particularly with regard to the role of expectations, niche theory and radical innovation, and the multi-level perspective on sociotechnical transitions.

Mentions

  • Middle Range Theory (MRT)
  • Science & Techology Studies (STS)
  • Merton introduced the notion of MRT in sociology in the three editions
    of Social Theory and Social Structure (1949, 1957, 1968).
    e.g.
    Merton, R.K. 1948. Discussion of Parsons’ `The position of sociological theory ‘. American Sociological Review 13(2): 164-168. Google Scholar

Aside

At the paywall, it is unclear who wrote the article.  The paywall declares that it was Frank W. Geels, but provides an “author biography” for Casper Bruun Jensen.

Yup, it is Frank W. Geels. Yet…

Casper Bruun Jensen is
  • Associate professor at the Technologies in Practice group, IT University of Copenhagen.
  • Casper Bruun Jensen, Ontologies for Developing Things (Sense, 2010)
  • Casper Bruun Jensen, Brit Ross Winthereik, Monitoring Movements in Development (MIT, 2013).

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Tracking the Digital Footprints of Personality | Lambiotte, Kosinski

Renaud Lambiotte, Michal Kosinski; Tracking the Digital Footprints of Personality; In Proceedings of the IEEE, Volume 102, Number 12; 2014-12; 5 pages; pdf (timeout? aclwalled?)
Teaser: This paper reviews literature showing how pervasive records of digital footprints can be used to infer personality.

Abstract

A growing portion of offline and online human activities leave digital footprints in electronic databases. Resulting big social data offers unprecedented insights into population-wide patterns and detailed characteristics of the individuals. The goal of this paper is to review the literature showing how pervasive records of digital footprints, such as Facebook profile, or mobile device logs, can be used to infer personality, a major psychological framework describing differences in individual behavior. We briefly introduce personality and present a range of works focusing on predicting it from digital footprints and conclude with a discussion of the implications of these results in terms of privacy, data ownership, and opportunities for future research in computational social science.

References

There are 54 references.

Network Diversity and Affect Dynamics: The Role of Personality Traits | Alshamsi, Pianesi, Lepri, Pentland, Rahwan

Aamena Alshamsi, Fabio Pianesi, Bruno Lepri, Alex Pentland, Iyad Rahwan; Network Diversity and Affect Dynamics: The Role of Personality Traits; In Public Library of Science | One (PLOS | One); 2016-04-01.DOI:10.1371/journal.pone.0152358

Abstract

People divide their time unequally among their social contacts due to time constraints and varying strength of relationships. It was found that high diversity of social communication, dividing time more evenly among social contacts, is correlated with economic well-being both at macro and micro levels. Besides economic well-being, it is not clear how the diversity of social communication is also associated with the two components of individuals’ subjective well-being, positive and negative affect. Specifically, positive affect and negative affect are two independent dimensions representing the experience (feeling) of emotions. In this paper, we investigate the relationship between the daily diversity of social communication and dynamic affect states that people experience in their daily lives. We collected two high-resolution datasets that capture affect scores via daily experience sampling surveys and social interaction through wearable sensing technologies: sociometric badges for face-to-face interaction and smart phones for mobile phone calls. We found that communication diversity correlates with desirable affect states–e.g. an increase in the positive affect state or a decrease in the negative affect state–for some personality types, but correlates with undesirable affect states for others. For example, diversity in phone calls is experienced as good by introverts, but bad by extroverts; diversity in face-to-face interaction is experienced as good by people who tend to be positive by nature (trait) but bad for people who tend to be not positive by nature. More broadly, the moderating effect of personality type on the relationship between diversity and affect was detected without any knowledge of the type of social tie or the content of communication. This provides further support for the power of unobtrusive sensing in understanding social dynamics, and in measuring the effect of potential interventions designed to improve well-being.

References

There are 57 refreences.

Users of the main smartphone operating systems (iOS, Android) differ only little in personality | Götz, Stieger, Reips

Friedrich M. Götz,, Stefan Stieger, Ulf-Dietrich Reips; Users of the main smartphone operating systems (iOS, Android) differ only little in personality; In Public Library of Science | One (PLOS | One); 2017-05-03; DOI:10.1371/journal.pone.0176921

Abstract

The increasingly widespread use of mobile phone applications (apps) as research tools and cost-effective means of vast data collection raises new methodological challenges. In recent years, it has become a common practice for scientists to design apps that run only on a single operating system, thereby excluding large numbers of users who use a different operating system. However, empirical evidence investigating any selection biases that might result thereof is scarce. Henceforth, we conducted two studies drawing from a large multi-national (Study 1; N = 1,081) and a German-speaking sample (Study 2; N = 2,438). As such Study 1 compared iOS and Android users across an array of key personality traits (i.e., well-being, self-esteem, willingness to take risks, optimism, pessimism, Dark Triad, and the Big Five). Focusing on Big Five personality traits in a broader scope, in addition to smartphone users, Study 2 also examined users of the main computer operating systems (i.e., Mac OS, Windows). In both studies, very few significant differences were found, all of which were of small or even tiny effect size mostly disappearing after sociodemographics had been controlled for. Taken together, minor differences in personality seem to exist, but they are of small to negligible effect size (ranging from OR = 0.919 to 1.344 (Study 1), ηp2 = .005 to .036 (Study 2), respectively) and may reflect differences in sociodemographic composition, rather than operating system of smartphone users.

References

There are 80 references.

Expectations in Technological Developments: An Example of Prospective Structures to be Filled in by Agency | van Lente, Rip

Harro van Lente, Arie Rip; Expectations in Technological Developments: An Example of Prospective Structures to be Filled in by Agency; 28 pages; ; OAI:oai:doc.utwente.nl:34732; landing, (a photocopy of a paper article) academia.edu, landing as Chapter 7; In Cornelis Disco, Barend vander Meulen, Getting New Technologies Together: Studies in Making Sociotechnical Order; Walter de Gruyter; 1998.

An earlier version of this paper was prepared, submitted, presented at the XXIth (21st?) World Congress of Sociology, ISA, Bielefield, DE, 1994-07-18.

Mentions

  • Agenda Theory (van Lente 1993)
  • <quote>The study of texts <snip/> in this sense, one can think of technology as a generalized text This is important <snip/> because texts are nothing if not internally coordinated, among other things because of their story-line.</quote>
  • Prospective Structure
  • Structure versus Agency
  • the “script”
  • Expectation (theory)
    <quote>expectations structure activity differently than structures normally do</quote>
  • <quote capitalization=”herein”>Prospective Structure hence has the same power as Forceful Fiction in opening up space for action.</quote>
Branded Theories
  • Functionalism
  • Interactionism
  • van Lente → Agenda Theory (his, theirs)
  • Mead → role-taking
  • Goffman → dramaturgical presentation of self
  • Berger & Luckman → social construction of reality
  • Giddens → structuration theory
  • Burns & Flam → social rule system theory
  • Shibutani → social processes
  • Strauss → social world
  • Boudon → transformation processes

Outline

  • Introduction
  • Technology and the Problem of Structure-Agency in Sociology
  • Some Examples of Emerging Patterns in Technology
    • Example 1: Moore’s Law as a Self-Fulfilling Prophecy.
    • Example 2: The Emerging World of Membrane Technology in The Netherlands.
    • Example 3: HDTV, a Self-Justifying Technology.
  • From Promise to Requirement
  • Mechanisms: Mutual Positioning and Agenda-Building
  • In Conclusion

Actualities

The Sociology of Expectations in Science and Technology | Borup, Brown, Konrad, van Lente

Mads Borup, Nik Brown, Kornelia Konrad, Harro Van Lente; The Sociology of Expectations in Science and Technology; an Editorial; In Technology Analysis & Strategic Management, Volume 18, Numbers 3/4, 285 –298, July – September, 2006-07; 14 pages; DOI:10.1080/09537320600777002; paywall; copy

Relevance

Claim: Moore’s law is a self-fulfilling prophecy; by stating the law and the “tick tock” roadmap, the vision is driven to successful eventuality.

Mentions

  • “The Hype Cycle,” The Gartner Group
    The metaphoric device of an underdamped oscillator applied to social processes.
    Hype Cycle, In Jimi Wales’ Wiki.

Concept

<quote>By definition, innovation in contemporary science and technology is an intensely future-oriented business with an emphasis on the creation of new opportunities and capabilities. Novel technologies and fundamental changes in scientific principle do not substantively pre-exist themselves, except and only in terms of the imaginings, expectations and visions that have shaped their potential. As such, future-oriented abstractions are among the most important objects of enquiry for scholars and analysts of innovation. Such expectations can be seen to be fundamentally ‘generative’, they guide activities, provide structure and legitimation, attract interest and foster investment. They give definition to roles, clarify duties, offer some shared shape of what to expect and how to prepare for opportunities and risks. Visions drive technical and scientific activity, warranting the production of measurements, calculations, material tests, pilot projects and models. As such, very little in innovation can work in isolation from a highly dynamic and variegated body of future-oriented understandings about the future.</quote>

<ahem>future-oriented understandings about the future.</ahem>

References

There are 49 bibliographic references.

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  44. Van Lente, op. cit., Ref. 1; Konrad, this issue.
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  46. C. Thompson, The biotech mode of reproduction, Paper prepared for the School of American Research Advanced Seminar ‘Animation and Cessation: Anthropological Perspectives on Changing Definitions of Life and Death in the Context of Biomedicine’, Santa Fe, New Mexico, 2000.
  47. P. Weingart, A. Engels & P. Pansegrau, Risks of communication: discourses on climate change in science, politics, and mass medi, Public Understanding of Science, 9(3), 2000, pp. 261–283.
  48. H. Nowotny, P. Scott & M. Gibbons, Re-thinking Science—Knowledge and the Public in an Age of Uncertainty (Cambridge, UK, Polity Press, 2001), p. 232.
  49. Brown et al., op. cit., Ref. 4.

Tom Insel is “The Smartphone Psychiatrist” at Mindstrong Health | The Atlantic

Tom Insel is “The Smartphone Psychiatrist” promoting his employer ‘Mindstrong’;
David Dobbs; In The Atlantic; 2017-07.

tl;dr → a promotion of Mindstrong Health, announcing $14M in funding today
tl;dr → a hagiogaphy of Dr. Thomas Insel, its public face.

Occasion

Mindstrong Health Raises $14 Million in Series-A Funding; press release; 2017-06-15.
Teaser: Founding team includes the former Director of the National Institute of Mental Health, Dr. Tom Insel, and former Director of the National Cancer Institute, Dr. Richard Klausner

Tom Insel
  • Mindstrong, startup, Palo Alto, CA
  • Product Manager (Director?), Verily (the ‘V’ in the Alphabet pantheon as Google’s “health” hobby).
  • (ex-)National Institute of Mental Health (NIMH).
  • other institutions in the article.
Mindstrong Health

At the bottom

Mentions

  • Diagnostic and Statistical Manual of Mental Disorders (DSM)
  • Verily of Google
    Mountain View, CA
  • Tom Insel
    • one of four brothers
    • curriculum vitae in the article
    • Pleasanton, CA
  • H. Herbert Insel
    • father of Tom Insel
    • an eye surgeon
    • Dayton, OH
  • clomipramine
  • OCD
  • prairie-vole
  • Insel, Wang, and Young
  • biology vs environment, teach the controversy (nature vs nurture)
  • Thomas Insel; Towards a New Understanding of Mental Illness; TED Talk, 2013.

Promotion

<quote>The force they hope to harness is the power of daily behavior, trackable through smartphone use, to reflect one’s mental health. As people start to slide into depression, for instance, they may do several of the following things easily sensed by a phone’s microphones, accelerometers, GPS units, and keyboards: They may talk with fewer people; and when they talk, they may speak more slowly, say less, and use clumsier sentences and a smaller vocabulary. They may return fewer calls, texts, emails, Twitter direct messages, and Facebook messages. They may pick up the phone more slowly, if they pick up at all, and they may spend more time at home and go fewer places. They may sleep differently. Someone slipping toward a psychotic state might show similar signs, as well as particular changes in syntax, speech rhythm, and movement.</quote>

Snide

<quote>Psychiatry has always struggled to be taken seriously as a science. By the 1980s, the field seemed especially lost. Its best drugs were from the 1950s and ’60s. Most of its hospitals, their failings made infamous by works such as Sylvia Plath’s The Bell Jar and Ken Kesey’s One Flew Over the Cuckoo’s Nest, had been closed. Talk therapy, which often works, but by psychobiological pathways painfully difficult to discern, was frequently lampooned. For these and other reasons, including its penchant for savage infighting, psychiatry in the ’70s was “a collection of diverse cults rather than a medical science,” as Melvin Sabshin, a onetime medical director of the American Psychiatric Association, later put it. </quote>

<quote>A therapist, the joke goes, knows in great detail how a patient is doing every Thursday at 3 o’clock.>/quote>

Background

Theory

the two components necessary to any approach to mental-health care—assessment

  1. collection and analysis of “data”
    • self-attested by the patient
    • logged by the phone
  2. intervention
    • informal social
    • medical support, inpatient
    • medical support, outpatient

prime, an app

  • prime → (Personalized Real-time Intervention for Motivation Enhancement
  • Danielle Schlosser
    • a clinical psychologist
    • recruited to Verily from the psychiatry department at UC San Francisco by Thomas Insel
    • developed prime. a monitoring app, for an outpatient’s phone
  • Concept
    Social proof to the cohort that they are all “normal” people who are able to “function.”
  • Applicable
    • people ages 14 to 30
    • recently diagnosed with schizophrenia
  • Feature-Function
    <paraphrase>

    1. modeled on Facebook
      i.e. a circle of ‘friends’
    2. connecting people so they can turn to one another for help, perspective, and affirmation.
    3. reading material → set of motivational essays, talks, and interactive modules
      [which] guide with decisions and review dilemmas common among the membership.
    4. monitoring & alerting → spotting emerging crises and responding with peer, social-service, and clinician support.

</paraphrase>

Mindstrong Health

  • co-founders
    • Richard Klausner
    • Paul Dagum
    • Michael Friberg
  • Palo Alto
  • something about 2017-05, probably the date of the interview for the article
  • Roles
    • Insel → expertise and connections in the mental-health field
    • Klausner → business
    • Dagum → data-analysis

Statement

<quote ref=”presser>Based in Palo Alto, California, Mindstrong’s patented science and technology was developed by Dr. Dagum, and is based on four years of extensive clinical studies applying machine intelligence to human-computer interactions patterns. Mindstrong products are in clinical trials in numerous partnership projects with payers, providers, academics and the pharmaceutical industry to bring these new tools to bear on answering the most fundamental questions in behavioral health. Its Board of Directors includes Richard Klausner, MD, Jim Tananbaum, MD, Robert Epstein, MD, Thomas Insel, MD, and Paul Dagum, MD PhD.</quote>

Concept

  • Mindstrong does assessment.
  • Mindstrong does “learning-based mental-health care.”
  • Mindstrong does continuous assessment and feedback [which] would drive the interventions.
  • Mindstrong does measurement-based practices [would be for] all therapies

<quote>Smartphones can track daily behaviors that reflect mental health. A phone can sense the beginning of a crisis and trigger an appropriate treatment response. This idea has been floating around Silicon Valley and mental-health circles for several years. Insel estimates that a good five or 10 other companies or research teams—including Verily—are trying to do something similar. Mindstrong hopes to gain an edge by combining Insel’s expertise and connections in the mental-health field with Klausner’s business experience and Dagum’s data-analysis tools and skills—and by moving quickly.</quote>

Plan

  • 2018 & 2019 → testing phone-based data-collection-and-analysis systems,
  • 2019 & 2020 → explore ways to partner with others to provide intervention.

Intellectual Property

three patents for a data-collection-and-analysis system for such purposes.
Paul Dagum designed this system [is a named inventor?]

Checkboxes

  • Mindstrong will collect information
  • Mindstrong will use an opt-in
  • Mindstrong will use encryption
    <quote>all data will be strongly encrypted</quote>
  • Mindstrong will use HIPPA<quote>All data will be firewalled according to strict patient-privacy practices.</quote>
  • Mindstrong will only store metadata
    • not
      • voice
      • typed
    • e.g.
      • semantic structures
      • repeated use of key words or phrases
      • estimated
      • emotional state
      • cognitive states,
        e.g.

        • depression,
        • mania,
        • psychosis,
        • cognitive confusion.

Competition

Verily (Google)

  • Andy Conrad, CEO
  • <quote>a 500-person company (Verily>part of a 74,000-person company (Alphabet)
  • South San Francisco

7 Cups

  • Has an app.
  • Another private venture.
  • Glen Moriarty, CEO
  • Insels daughter NAME is an employee.
  • Demographic
    • young
    • diverse
    • 90% are under the age of 35
    • “likely to go underserved by traditional mental-health care.”
  • Applies DASS‑21Anonymizes the results.
Concept

<quote>7 Cups provides text-based peer counseling and support for people with depression or anxiety or a long list of other conditions. Registering for the simpler services, such as peer connection, takes only seconds, and users can also get referrals to either coaches or licensed mental-health counselors and psychologists.</quote>

DASS‑21

DASS-21 → Depression Anxiety Stress Scales

DASS, University of New South Wales, AU

There is a manual

Questions

How to Call B.S. on Big Data: A Practical Guide | New Yorker

How to Call B.S. on Big Data: A Practical Guide; ; In The New Yorker/ 2017-06-03.

Occasion

INFO 198/BIOL 106B (callingbullshit.org) – “Calling Bullshit in the Age of Big Data,” a course, University of Washington (Washington State, that is, located in Seattle WA). Instructors:  Jevin West (iinformation), Carl Bergstrom (biology)

Mentions

Referenced

Previously

In The New  Yorker

De-Anonymizing Web Browsing Data with Social Networks | Su, Shukla, Goel, Narayanan

Jessica Su, Ansh Shukla, Sharad Goel, Arvind Narayanan; De-Anonymizing Web Browsing Data with Social Networks; draft; In Some Venue Surely (they will publish this somewhere, it is so very nicely formatted); 2017-05; 9 pages.

Abstract

Can online trackers and network adversaries de-anonymize web browsing data readily available to them? We show—theoretically, via simulation, and through experiments on real user data—that de-identified web browsing histories can be linked to social media profiles using only publicly available data. Our approach is based on a simple observation: each person has a distinctive social network, and thus the set of links appearing in one’s feed is unique. Assuming users visit links in their feed with higher probability than a random user, browsing histories contain tell-tale marks of identity. We formalize this intuition by specifying a model of web browsing behavior and then deriving the maximum likelihood estimate of a user’s social profile. We evaluate this strategy on simulated browsing histories, and show that given a history with 30 links originating from Twitter, we can deduce the corresponding Twitter profile more than 50% of the time. To gauge the real-world effectiveness of this approach, we recruited nearly 400 people to donate their web browsing histories, and we were able to correctly identify more than 70% of them. We further show that several online trackers are embedded on sufficiently many websites to carry out this attack with high accuracy. Our theoretical contribution applies to any type of transactional data and is robust to noisy observations, generalizing a wide range of previous de-anonymization attacks. Finally, since our attack attempts to find the correct Twitter profile out of over 300 million candidates, it is—to our knowledge—the largest-scale demonstrated de-anonymization to date.

Promotions

  • Ad Networks Can Personally Identify Web Users; Wendy Davis; In MediaPost; 2017-01-20.
    <quote> The authors tested their theory by recruiting 400 people who allowed their Web browsing histories to be tracked, and then comparing the sites they visited to sites mentioned in Twitter accounts they followed. The researchers say they were able to use that method to identify more than 70% of the volunteers.</quote>