�ݺ�ߣ

Editor's Notes

• #2: Objects tend to around their centers of mass.
• #3: My own layers, at the level of me, doing research to try to do many things at once: do ethngoraphy, intervene, teach, and challenge frames for “what counts” as valuable in academic settings: Arrow 1: Data, “big data,” and datafication *complicates the situation we study *complicates what counts as data *complicates how our research might be used …among other things Arrow 2: Methodogical practice *From object to flow to try to grapple with the complexity of networked sociality *Remix methods as a way of avoiding the baggage of classic method terminology *network sensibility as a way of focusing on movement, connections, relations versus objects, outcomes, and linearity *Creative fabrication as ethical protection of data and privacy in digitally-mediated social contexts *Giving credit to participants who are partners rather than research subjects Criteria and evaluation of Quality Today’s ethnographic work should be evaluated along much broader and more complex lines than has been traditional in academic and scientific communities THIS IS NOT DISSEMINATION BUT ACTIVIST ENGAGEMENT *intervention, action, pedagogy *alternative and open access publishing *reputation building through public intellectual engagement (boyd, crawford, tufecki) Discourse Matters *terminology influence how we frame, design, enact, *new terms to evoke different responses for computer scientists (or as many of them call themselves now, machine learning specialists) Data mining, predictive analytics Ethics versus creepy factor Studying what has been versus intervening in what we want to become
• #4: My own layers, at the level of me, doing research to try to do many things at once: do ethngoraphy, intervene, teach, and challenge frames for “what counts” as valuable in academic settings: Arrow 1: Data, “big data,” and datafication *complicates the situation we study *complicates what counts as data *complicates how our research might be used …among other things Arrow 2: Methodogical practice *From object to flow to try to grapple with the complexity of networked sociality *Remix methods as a way of avoiding the baggage of classic method terminology *network sensibility as a way of focusing on movement, connections, relations versus objects, outcomes, and linearity *Creative fabrication as ethical protection of data and privacy in digitally-mediated social contexts *Giving credit to participants who are partners rather than research subjects Criteria and evaluation of Quality Today’s ethnographic work should be evaluated along much broader and more complex lines than has been traditional in academic and scientific communities THIS IS NOT DISSEMINATION BUT ACTIVIST ENGAGEMENT *intervention, action, pedagogy *alternative and open access publishing *reputation building through public intellectual engagement (boyd, crawford, tufecki) Discourse Matters *terminology influence how we frame, design, enact, *new terms to evoke different responses for computer scientists (or as many of them call themselves now, machine learning specialists) Data mining, predictive analytics Ethics versus creepy factor Studying what has been versus intervening in what we want to become
• #5: Venn 1: Layers of Political complexity (a’la different goals, different futures, different stakeholders, multiciplicity of method) Commodification of inquiry (Horst); Venn 2: Research(er) sensibilities (network, big data, inductive/emergent vs hypothetico deductive Venn 3: Goal of inquiry practice (e.g., scope/partners (Lanzeni Ardevol); Stakeholder ethnography “in there” with us (Pink)… Venn 4: Epistemological ad Ontological Frames (distributive versus accumulative (Tom); intervene vs. understand (Friere); So I don’t need to cover this, but refer to previous presentations. Rather: FIRST, a matter of critque, ABOVE AND BELOW Differing goals, different visions of the future (Sarah) Commodification of inquiry (Heather) BELOW: practices and procedures of inquiry. Gardening. Crime scene investigation. Surveys of social media use among teens, ethnographies of health technologies in practice. I also mean practical and logistic activities of making decision about who to study, when, where, and how. What questions we ask in interviews, whether we do interviews or observations or have participants keep their own diaries of everyday use of technologies. I also mean those things we don’t generally think of as “method,” in that it is not directly validated as data collection or data analysis. Like finding books randomly on the library shelves that influence your conceptualization of a problem. Like “cleaning up” data so that it doesn’t contain the stuff that seems like “noise” or “irrelevant information.” Like doodling, drawing maps or connecting concepts visually on scratch paper. Like changing your mind in the middle of a study.   LATER, a matter of remixing processes and goals, ABOVE AND BELOW
• #6: Venn 1: Layers of Political complexity (a’la different goals, different futures, different stakeholders, multiciplicity of method) Commodification of inquiry (Horst); Venn 2: Research(er) sensibilities (network, big data, inductive/emergent vs hypothetico deductive Venn 3: Goal of inquiry practice (e.g., scope/partners (Lanzeni Ardevol); Stakeholder ethnography “in there” with us (Pink)… Venn 4: Epistemological ad Ontological Frames (distributive versus accumulative (Tom); intervene vs. understand (Friere); So I don’t need to cover this, but refer to previous presentations. Rather: FIRST, a matter of critque, ABOVE AND BELOW Differing goals, different visions of the future (Sarah) Commodification of inquiry (Heather) BELOW: practices and procedures of inquiry. Gardening. Crime scene investigation. Surveys of social media use among teens, ethnographies of health technologies in practice. I also mean practical and logistic activities of making decision about who to study, when, where, and how. What questions we ask in interviews, whether we do interviews or observations or have participants keep their own diaries of everyday use of technologies. I also mean those things we don’t generally think of as “method,” in that it is not directly validated as data collection or data analysis. Like finding books randomly on the library shelves that influence your conceptualization of a problem. Like “cleaning up” data so that it doesn’t contain the stuff that seems like “noise” or “irrelevant information.” Like doodling, drawing maps or connecting concepts visually on scratch paper. Like changing your mind in the middle of a study.   LATER, a matter of remixing processes and goals, ABOVE AND BELOW