Topic: Generalizability

Seminar
2 seminars

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SeminarPsychology

Inclusive Human Participant Research

Pollyanna Sheehan, Arnelle Etiennt
University of Bristol, Carnegie Mellon University
Jun 23, 2021

Human participant research is somehow both antithetical and complementary to science. On the one hand, working with human participants provides incredibly rich and complex data with ‘real-world’ ecological validity. On the other, this richness is due to the incredible number of variables which uncontrollably become intertwined with your research interest, potentially limiting the conclusions you can draw from your work. Historical over-representation of white men as research participants, coupled with often overly-stringent exclusion criteria has led to a diversity crisis in human participant research. For our research to be truly inclusive, representative and generalisable to the rest of the population, our data must be collected from diverse individuals. This session will explore common barriers to diversity in studies with human participants, and will provide guidance on how to make sure your own research is accessible and inclusive.

SeminarPsychology

A Manifesto for Big Team Science

Patrick S Forscher
Université Grenoble Alpes
Mar 11, 2021

Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, I argue that these five challenges share a common cause: insufficient investment of resources into the typical psychology study. I further suggest that big team science can help address these challenges by allowing researchers to pool their resources to efficiently and drastically increase the amount of resources available for a single study. However, the current incentives, infrastructure, and institutions in academic science have all developed under the assumption that science is conducted by solo Principal Investigators and their dependent trainees. These barriers must be overcome if big team science is to be sustainable. Big team science likely also carries unique risks, such as the potential for big team science institutions to monopolize power, become overly conservative, make mistakes at a grand scale, or fail entirely due to mismanagement and a lack of financial sustainability. I illustrate the promise, barriers, and risks of big team science with the experiences of the Psychological Science Accelerator, a global research network of over 1400 members from 70+ countries.

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