Karthik Panchanathan

Curriculum vitae

Department of Anthropology

University of Missouri

112 Swallow Hall
Columbia, MO 65211

Honest signaling in academic publishing

Journal article

Leonid Tiokhin, Karthik Panchanathan, Daniel Lakens, Simine Vazire, Thomas Morgan, Kevin Zollman
PloS one, vol. 16, 2021, pp. e0246675

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APA   Click to copy
Tiokhin, L., Panchanathan, K., Lakens, D., Vazire, S., Morgan, T., & Zollman, K. (2021). Honest signaling in academic publishing. PloS One, 16, e0246675.

Chicago/Turabian   Click to copy
Tiokhin, Leonid, Karthik Panchanathan, Daniel Lakens, Simine Vazire, Thomas Morgan, and Kevin Zollman. “Honest Signaling in Academic Publishing.” PloS one 16 (2021): e0246675.

MLA   Click to copy
Tiokhin, Leonid, et al. “Honest Signaling in Academic Publishing.” PloS One, vol. 16, 2021, p. e0246675.

BibTeX   Click to copy

  title = {Honest signaling in academic publishing},
  year = {2021},
  journal = {PloS one},
  pages = {e0246675},
  volume = {16},
  author = {Tiokhin, Leonid and Panchanathan, Karthik and Lakens, Daniel and Vazire, Simine and Morgan, Thomas and Zollman, Kevin}


Academic journals provide a key quality-control mechanism in science. Yet, information asymmetries and conflicts of interests incentivize scientists to deceive journals about the quality of their research. How can honesty be ensured, despite incentives for deception? Here, we address this question by applying the theory of honest signaling to the publication process. Our models demonstrate that several mechanisms can ensure honest journal submission, including differential benefits, differential costs, and costs to resubmitting rejected papers. Without submission costs, scientists benefit from submitting all papers to high-ranking journals, unless papers can only be submitted a limited number of times. Counterintuitively, our analysis implies that inefficiencies in academic publishing (e.g., arbitrary formatting requirements, long review times) can serve a function by disincentivizing scientists from submitting low-quality work to high-ranking journals. Our models provide simple, powerful tools for understanding how to promote honest paper submission in academic publishing.


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