The Influence of Social Comparison on Visual Representation of One's Face

Can the effects of social comparison extend beyond explicit evaluation to visual self-representation—a perceptual stimulus that is objectively verifiable, unambiguous, and frequently updated? We morphed images of participants' faces with attractive and unattractive references. With access to a mirror, participants selected the morphed image they perceived as depicting their face. Participants who engaged in upward comparison with relevant attractive targets selected a less attractive morph compared to participants exposed to control images (Study 1). After downward comparison with relevant unattractive targets compared to control images, participants selected a more attractive morph (Study 2). Biased representations were not the products of cognitive accessibility of beauty constructs; comparisons did not influence representations of strangers' faces (Study 3). We discuss implications for vision, social comparison, and body image

The growth and gaps of genetic data sharing policies in the United States

The 1996 Bermuda Principles launched a new era in data sharing, reflecting a growing belief that the rapid public dissemination of research data was crucial to scientific progress in genetics. A historical review of data sharing policies in the field of genetics and genomics reflects changing scientific norms and evolving views of genomic data, particularly related to human subjects’ protections and privacy concerns. The 2013 NIH Draft Genomic Data Sharing (GDS) Policy incorporates the most significant protections and guidelines to date. The GDS Policy, however, will face difficult challenges ahead as geneticists seek to balance the very real concerns of research participants and the scientific norms that propel research forward. This article provides a novel evaluation of genetic and GDS policies’ treatment of human subjects’ protections. The article examines not only the policies, but also some of the most pertinent scientific, legal, and regulatory developments that occurred alongside data sharing policies. This historical perspective highlights the challenges that future data sharing policies, including the recently disseminated NIH GDS Draft Policy, will encounter

Trust, vulnerable populations, and genetic data sharing

Recent policies and proposed regulations, including the Notice of Proposed Rulemaking for the Common Rule and the 2014 NIH Genetic Data Sharing Policy, seek to improve research subject protections. Protections for subjects whose genetic data is shared are critical to reduce risks such as loss of confidentiality, stigma, and discrimination. In the article ‘It depends whose data are being shared: considerations for genomic data sharing policies’, Robinson et al. provide a response to our article, ‘The Growth and Gaps of Genetic Data Sharing Policies’. Robinson et al. highlight the importance of individual and group preferences. In this article, we extend the conversation on models for improving protections which will mitigate consequences for individuals and groups that are vulnerable to stigma and discrimination

Codifying Collegiality: Recent Developments in Data Sharing Policy in the Life Sciences

<div><p>Over the last decade, there have been significant changes in data sharing policies and in the data sharing environment faced by life science researchers. Using data from a 2013 survey of over 1600 life science researchers, we analyze the effects of sharing policies of funding agencies and journals. We also examine the effects of new sharing infrastructure and tools (i.e., third party repositories and online supplements). We find that recently enacted data sharing policies and new sharing infrastructure and tools have had a sizable effect on encouraging data sharing. In particular, third party repositories and online supplements as well as data sharing requirements of funding agencies, particularly the NIH and the National Human Genome Research Institute, were perceived by scientists to have had a large effect on facilitating data sharing. In addition, we found a high degree of compliance with these new policies, although noncompliance resulted in few formal or informal sanctions. Despite the overall effectiveness of data sharing policies, some significant gaps remain: about one third of grant reviewers placed no weight on data sharing plans in their reviews, and a similar percentage ignored the requirements of material transfer agreements. These patterns suggest that although most of these new policies have been effective, there is still room for policy improvement.</p></div

Characteristics of survey respondents.

<p>Note: Percentages may not sum to 100% because of item non-response.</p><p>Characteristics of survey respondents.</p

Effect of data sharing tools progress of research.

<p>Effect of data sharing tools progress of research.</p

Influence of policies on data sharing.

<p>Influence of policies on data sharing.</p