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In this article, we present the potentials of Google Vision API-based networks for studying online images, covering three important modalities as part of a critical visual methodology: the content of the image itself, its specific ‘audiencing’ through web references (or image metadata), and the sites of image circulation. First, we conceptually and technically define different networks built upon computer vision features: image-label, image-web entities, and image-domain. Second, we present a research protocol diagram that illustrates how to build networks of images and respective descriptions or sites of circulation. Third, we discuss the potentialities of computer vision networks as a research device, stressing their data-relational (trans)formations and interpretative specifics. Three different case studies will be introduced as examples. In conclusion, we argue that such a visual methodology requires critical technical practices accounting for the multiple layers of technical mediation involved.

Objectives: The authors sought to ascertain the details of medical school policies about relationships between drug companies and medical students as well as student affairs deans' attitudes about these interactions. Methods: In 2005, the authors surveyed deans and student affairs deans at all U.S. medical schools and asked whether their schools had a policy about relationships between drug companies and medical students. They asked deans at schools with policies to summarize them, queried student affairs deans regarding their attitudes about gifts, and compared their attitudes with those of students who were studied previously. Results: Independently of each other, 114 out of 126 deans (90.5%) and 114 out of 126 student affairs deans (90.5%) responded (identical numbers are not misprints). Ten schools had a policy regarding relationships between medical students and drug company representatives. Student affairs deans were much more likely than students to perceive that gifts were inappropriate. Conclusion: These 2005 policies show trends meriting review by current medical schools in considering how to comply with the 2008 Association of American Medical Colleges recommendations about relationships between drug companies and medical students or physicians.

Thematic analysis of critical incidents interviews with 13 physician coaches yielded two orientations to coaching: reflection/teaching coaches focused on others and described positive encounters experienced in coaching; personal learning and change coaches identified more personal benefits from the experience. (Contains 31 references.) (SK)

Third-year medical student's exposure to and attitudes about drug company interactions are measured. Student experiences and attitudes suggest that as a group they are at risk unrecognized influence by marketing efforts.

In this article, we present the potentials of Google Vision API-based networks for studying online images, covering three important modalities as part of a critical visual methodology: the content of the image itself, its specific ‘audiencing’ through web references (or image metadata), and the sites of image circulation. First, we conceptually and technically define different networks built upon computer vision features: image-label, image-web entities, and image-domain. Second, we present a research protocol diagram that illustrates how to build networks of images and respective descriptions or sites of circulation. Third, we discuss the potentialities of computer vision networks as a research device, stressing their data-relational (trans)formations and interpretative specifics. Three different case studies will be introduced as examples. In conclusion, we argue that such a visual methodology requires critical technical practices accounting for the multiple layers of technical mediation involved. [ABSTRACT FROM AUTHOR]