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Research Article

Disparate foundations of scientists’ policy positions on contentious biomedical research

Achim Edelmann, James Moody, and Ryan Light
  1. aInstitute of Sociology, University of Bern, 3012 Bern, Switzerland;
  2. bDuke Network Analysis Center, Duke University, Durham, NC 27708;
  3. cDepartment of Sociology, Duke University, Durham, NC 27708;
  4. dKing Abdulaziz University, Jeddah 21589, Saudi Arabia;
  5. eDepartment of Sociology, University of Oregon, Eugene, OR 97403

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PNAS first published May 30, 2017; https://doi.org/10.1073/pnas.1613580114
Achim Edelmann
aInstitute of Sociology, University of Bern, 3012 Bern, Switzerland;
bDuke Network Analysis Center, Duke University, Durham, NC 27708;
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  • For correspondence: achim.edelmann@gmail.com
James Moody
bDuke Network Analysis Center, Duke University, Durham, NC 27708;
cDepartment of Sociology, Duke University, Durham, NC 27708;
dKing Abdulaziz University, Jeddah 21589, Saudi Arabia;
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Ryan Light
eDepartment of Sociology, University of Oregon, Eugene, OR 97403
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  1. Edited by Peter S. Bearman, Columbia University, New York, NY, and approved April 21, 2017 (received for review September 1, 2016)

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  1. Fig. 1.
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    Fig. 1.

    Collaboration and position on gain-of-function research. (A) Scientists’ collaboration network. Nodes are petition signers, and edges are collaborations; layout via Fruchterman–Reingold, which tends to place scientists near collaborators; node size is proportionate to the total number of collaborators; n = 378. (B) Predicted probabilities of signing the SFS petition by number of collaborators who signed either the SFS (green) or CWG (orange) petition. Probabilities are based on logistic regression models (SI Appendix, Table S3); the shaded area represents the 95% CI for the “all controls” model (SI Appendix, Model 6 in Table S3), which adjusts for specialization, publication volume, and demographic characteristics; n = 378.

  2. Fig. 2.
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    Fig. 2.

    Correspondence between research topics and position on gain-of-function research. Map of the largest component of scientists’ paper-to-paper coterm network: edges link papers (n = 19,257) weighted by their cosine similarity (see the SI Appendix for details); layout is via Fruchterman–Reingold, which places similar papers near one another; layout positions are constant in both A and B. (A) Edges colored by papers’ highest loading topic (eight colors, corresponding labels positioned near the center of topic clusters). (B) Edges colored by the authors’ camp (green, SFS; orange, CWG).

  3. Fig. 3.
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    Fig. 3.

    Effect of topic specialization on supporting SFS. Logistic regression model predicted probabilities of signing the SFS petition as a function of the average author topic loadings; figures extend on the x axis to the observed topic maximum; blue lines and 95% CIs (shaded area) are based on the “all controls” model, which adjusts for specialization, publication volume, and demographic characteristics (SI Appendix, Model 6 in Table S3). For comparison, the red dotted lines represent the bivariate associations, and the green dashed lines represent the trimmed model with highest Akaike information criterion (AIC) (excludes some topics); n = 378.

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When scientists take a stand on contentious issues
Achim Edelmann, James Moody, Ryan Light
Proceedings of the National Academy of Sciences May 2017, 201613580; DOI: 10.1073/pnas.1613580114

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When scientists take a stand on contentious issues
Achim Edelmann, James Moody, Ryan Light
Proceedings of the National Academy of Sciences May 2017, 201613580; DOI: 10.1073/pnas.1613580114
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