The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
The Temporal Structure of Scientific Consensus Formation
Open accessAbstract
This article engages with problems that are usually opaque: What trajectories do scientific debates assume, when does a scientific community consider a proposition to be a fact, and how can we know that? We develop a strategy for evaluating the state of scientific contestation on issues. The analysis builds from Latour’s black box imagery, which we observe in scientific citation networks. We show that as consensus forms, the importance of internal divisions to the overall network structure declines. We consider substantive cases that are now considered facts, such as the carcinogenicity of smoking and the non-carcinogenicity of coffee. We then employ the same analysis to currently contested cases: the suspected carcinogenicity of cellular phones, and the relationship between vaccines and autism. Extracting meaning from the internal structure of scientific knowledge carves a niche for renewed sociological commentary on science, revealing a typology of trajectories that scientific propositions may experience en route to consensus.
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Citations
Cites
Modularity and community structure in networks
Newman, M. E. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601602103 · Cited by 12,256
Falsification and the Methodology of Scientific Research Programmes
Lakatos, I. (1970) · Criticism and the Growth of Knowledge · doi:10.1017/cbo9781139171434.009 · Cited by 4,649
(2004) · doi:10.4324/9780203413845 · Cited by 2,963
Garfield, E. (1972) · Science · doi:10.1126/science.178.4060.471 · Cited by 2,788 · cited 1×
“Since Price (1965) suggested that the degree distribution of citations could point to important papers and journals, network analysis has become prominent in evaluating journals’ importance (Garfield 1972) and inducing mappings of science (Moody 2004).”
BackgroundThe Scientific Consensus on Climate Change
Oreskes, N. (2004) · Science · doi:10.1126/science.1103618 · Cited by 1,814
The specificity of the scientific field and the social conditions of the progress of reason
Bourdieu, P. (1975) · Social Science Information · doi:10.1177/053901847501400602 · Cited by 1,483
Pandora’s Hope: Essays on the Reality of Science Studies
(1999) · Choice Reviews Online · doi:10.5860/choice.37-1511 · Cited by 1,428
The effect of opinion clustering on disease outbreaks
Salathé, M., & Bonhoeffer, S. (2008) · Journal of The Royal Society Interface · doi:10.1098/rsif.2008.0271 · Cited by 238
Cited by
Van Dam, N. T., van Vugt, M. K., Vago, D. R., Schmalzl, L., Saron, C. D., Olendzki, A., Meissner, T., Lazar, S. W., Kerr, C. E., Gorchov, J., et al. (2018) · Perspectives on Psychological Science · doi:10.1177/1745691617709589 · Cited by 1,506
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., et al. (2018) · Science · doi:10.1126/science.aao0185 · Cited by 1,497
Public health and online misinformation: challenges and recommendations
Swire-Thompson, B., & Lazer, D. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094127 · Cited by 1,170
Computational Social Science and Sociology
Edelmann, A., Wolff, T., Montagne, D., & Bail, C. A. (2020) · Annual Review of Sociology · doi:10.1146/annurev-soc-121919-054621 · Cited by 305
An empirical examination of echo chambers in US climate policy networks
Jasny, L., Waggle, J., & Fisher, D. R. (2015) · Nature Climate Change · doi:10.1038/nclimate2666 · Cited by 227
Metadata
- Authors
- Shwed, U., & Bearman, P. S.
- Venue
- American Sociological Review
- Publisher
- SAGE Publications
- Published
- 2010-12
- Volume
- 75
- Issue
- 6
- Pages
- 817-840
- ISSN
- 0003-1224 (ISSN-L)
- 1939-8271
- OpenAlex
- W2150385690
- Cited by
- 336
- References
- 8
- FWCI
- 9.92
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
