One connector, four scholarly indexes, real DOIs and legal free PDFs. Works in Claude and ChatGPT.
Paste it into Claude or ChatGPT as a custom connector. 3-day free trial.
Olivia Guest, Andrea E. Martin
Psychology endeavors to develop theories of human capacities and behaviors based on a variety of methodologies and dependent measures. We argue that one of the most divisive factors in our field is whether researchers choose to employ computational modeling of theories (over and above data) during the scientific inference process. Modeling is undervalued, yet holds promise for advancing psychological science. The inherent demands of computational modeling guide us towards better science by forcing us to conceptually analyze, specify, and formalise intuitions which otherwise remain unexamined — what we dub “open theory”. Constraining our inference process through modeling enables us to build explanatory and predictive theories. Herein, we present scientific inference in psychology as a path function, where each step shapes the next. Computational modeling can constrain these steps, thus advancing scientific inference over and above stewardship of experimental practice (e.g., preregistration). If psychology continues to eschew computational modeling, we predict more replicability “crises” and persistent failure at coherent theory-building. This is because without formal modelling we lack open and transparent theorising. We also explain how to formalise, specify, and implement a computational model, emphasizing that the advantages of modeling can be achieved by anyone with benefit to all.
Formatted from the source metadata, not typed by hand. For a whole reference list, use the citation generator or ask your assistant through Find Research.
Guest, O., & Martin, A. E. (2021). How Computational Modeling Can Force Theory Building in Psychological Science. Perspectives on Psychological Science, 16(4), 789–802. https://doi.org/10.1177/1745691620970585
Guest, Olivia, and Andrea E. Martin. "How Computational Modeling Can Force Theory Building in Psychological Science." Perspectives on Psychological Science, vol. 16, no. 4, 2021, pp. 789–802, https://doi.org/10.1177/1745691620970585.
Guest, Olivia, and Andrea E. Martin. "How Computational Modeling Can Force Theory Building in Psychological Science." Perspectives on Psychological Science 16, no. 4 (2021): 789–802. https://doi.org/10.1177/1745691620970585.
Guest O., Martin A. E. How Computational Modeling Can Force Theory Building in Psychological Science // Perspectives on Psychological Science. — 2021. — Vol. 16, № 4. — P. 789–802. — URL: https://doi.org/10.1177/1745691620970585
@article{guest2021computational,
title = {{How Computational Modeling Can Force Theory Building in Psychological Science}},
author = {Olivia Guest and Andrea E. Martin},
journal = {Perspectives on Psychological Science},
year = {2021},
volume = {16},
number = {4},
pages = {789--802},
doi = {10.1177/1745691620970585},
url = {https://doi.org/10.1177/1745691620970585}
}TY - JOUR AU - Guest, Olivia AU - Martin, Andrea E. TI - How Computational Modeling Can Force Theory Building in Psychological Science JO - Perspectives on Psychological Science VL - 16 IS - 4 SP - 789 EP - 802 PY - 2021 DA - 2021/01/22 DO - 10.1177/1745691620970585 UR - https://doi.org/10.1177/1745691620970585 ER -
Add Find Research to Claude or ChatGPT and ask in plain language. The assistant reads this record, finds the papers around it and cites only what it actually found:
Setup takes about a minute: add the connector, then start the free trial.
Record from OpenAlex; open-access location from Unpaywall and the indexes. Find Research links only to legal copies.